Science topic

Security - Science topic

Security is the degree of protection against danger, damage, loss, and crime. Security as a form of protection are structures and processes that provide or improve security as a condition.
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What are the implications of the ongoing war in Ukraine for European security and global governance?
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While the implications of the war in Ukraine for European security and global governance are still unfolding it has become clear that the war has had a profound impact on the international landscape.
The war has shown that Europe is no longer immune to major military conflict. It has also shown that the post-World War II order of global governance is under strain.
The future of European security and global governance will depend on the outcome of the war in Ukraine. If Russia is successful in achieving its objectives in Ukraine, it will embolden other authoritarian regimes and make the world a more dangerous place. However, if Ukraine is able to defend itself and defeat Russia, it will send a strong message that aggression will not be tolerated.
The war in Ukraine has also highlighted the need for Europe to strengthen its security and energy independence. It has also shown that the West needs to cooperate more closely to counter the threat posed by Russia and other authoritarian regimes.
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if you want you can give me examples, they would help me in writing mythesis
thank you
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You may want to look over some helpful information presented below:
When one parent has a secure attachment style while the other has an ambivalent, disorganized, or avoidant attachment style, it can create challenges in a parenting relationship. However, it's important to remember that attachment styles are not set in stone, and individuals can change and develop more secure attachment patterns with time and effort. Here are some steps to help remedy the situation:
  1. Open and Honest Communication: Encourage open and non-judgmental communication between both parents. Discuss your attachment styles and how they might be affecting your parenting dynamics. The goal is to create a safe space for sharing feelings and experiences.
  2. Educate Yourselves: Both parents should learn more about attachment theory and how it can impact parenting. Understanding the underlying dynamics can help parents become more aware of their own attachment patterns and how they affect their children.
  3. Seek Professional Help: If the attachment styles are causing significant conflict or negatively impacting the children, consider seeking the guidance of a therapist or counselor who specializes in attachment issues. Family therapy can be particularly helpful in addressing these concerns.
  4. Individual Therapy: If one parent has an ambivalent, disorganized, or avoidant attachment style, they may benefit from individual therapy to explore and work on their attachment patterns. Therapy can help individuals understand the roots of their attachment style and develop more secure ways of relating to their children.
  5. Co-Parenting Classes: Consider attending co-parenting classes or workshops that focus on effective communication, conflict resolution, and parenting skills. These can provide practical strategies for improving the co-parenting relationship.
  6. Consistency: Strive for consistency in parenting practices between both parents, even if their attachment styles differ. Children benefit from knowing what to expect and experiencing stability in their caregiving relationships.
  7. Put the Child First: Always prioritize the best interests of the child. Both parents should be willing to adapt and make changes to provide a supportive and loving environment for their children, even if it means stepping outside their comfort zones.
  8. Practice Mindfulness: Mindfulness techniques can help both parents become more aware of their emotions and reactions. Mindfulness can assist in reducing reactivity and improving emotional regulation, which can benefit the parenting relationship.
  9. Empathy and Understanding: Each parent should make an effort to understand the other's perspective and challenges related to their attachment style. Developing empathy for each other's experiences can foster cooperation and compromise.
  10. Model Healthy Relationships: Strive to model healthy interpersonal relationships, including communication, empathy, and emotional support, for your children. Children often learn about relationships by observing their parents.
It's important to remember that change takes time, and addressing attachment-related issues in a parenting relationship is a process. Patience, empathy, and a willingness to work together for the well-being of the children are essential components of any effort to remedy such a situation.
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Can deep learning be harnessed to predict and prevent zero-day attacks in cloud environments, bolstering overall security posture?
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That is an excellent answer, Len. With your permission, I have copied and pasted it into my files.
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Hello Folks!
IoT security is becoming a key area of research these days. However, to move into a certain direction of research is hard to decide before knowing its value in the future.
What do you think? What are the new trends and hot topics in IoT security?
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iRecently, one very popular topic of research that joins together IoT, security and machine learning is detection of anomalies (malicious or technical) from network traffic. In the past anomaly detection was more restricted to malware, and used mostly signature-based and behavior-based methods. Current, machine-learning methos have taken over the state of the art and are not restricted to malware or malicious attacks, but can detect operational problems and other physical failures of the system. It is not restricted to IoT, but as many network topics, IoT scalated existing problems with sheer numbers and network heterogeneity.
If you look for papers with any combination of the following keywords, you will find an increasingly big number of studies:
Anomaly detection, network traffic, ids, ddos, machine-learning, classification and mitigation.
Finally, a very popular survey on the topic can be found below:
FFFFFinally,
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How are food and nutrition security important and factors on which food security depends and what are the pillars of food security?
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That is, nutrition security means having consistent access, availability, and affordability of foods and beverages that promote well-being and prevent disease, particularly among racial/ethnic minority populations, lower incomes populations, and rural and remote populations. Food security occurs when all people, all of the time, have access to sufficient, safe, affordable, and nutritious food for a healthy diet. Demand for food is increasing, driven by a range of population and demographic changes: population growth, changes in population structure, consumption growth, and urbanization. Food security focuses on quantity of food which is important but limited in scope. It is essential to talk about nutrition security now as preventable diet-related diseases are on the rise. Diabetes and obesity rates continue to rise, especially among children. Overall, National Food Security is crucial for National Security in India as it provides its people stability, growth, and assurance of food resources. National Food Security is also essential for India's economic growth since its population depends on agriculture production and distribution for their livelihoods. Food security can exist even when one of its pillars, availability, affordability, and accessibility, is absent. Food security exists when all people, at all times, have physical, social, and economic access to sufficient, safe, and nutritious food. The four pillars of food security are: food availability, access to food, utilization and stability. The nutritional dimension is integral to the concept of food security. Food insecurity creates enormous strain on worker productivity, healthcare spending, and military readiness and disproportionately impacts racial/ethnic minority populations, lower income populations, and rural and remote populations.Food security is when a person is able to obtain a sufficient amount of healthy food on a day-to-day basis. People who do not consume enough food each day suffer from food insecurity, which is when a person is unable to obtain a sufficient amount of healthy food on a day-to-day basis. The concept of food security has evolved to recognize the centrality of agency and sustainability, along with the four other dimensions of availability, access, utilization, and stability. These six dimensions of food security are reinforced in conceptual and legal understandings of the right to food.
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The use of AI and mapping technologies in laboratory settings raises a number of security concerns that must be addressed in order to ensure the integrity, confidentiality, and availability of data and resources. Data privacy and confidentiality, data integrity, access controls, network security, and so on are some of the security challenges.
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Yes, there are privacy and security considerations that need to be addressed when using AI for laboratory mapping or any application involving the collection, processing, and analysis of data, especially in sensitive environments like research laboratories. Here are some key considerations:
1. Data Privacy:
  • Data Collection: Ensure that any data collected for laboratory mapping is done in compliance with applicable data privacy regulations (e.g., GDPR, HIPAA). Obtain informed consent from individuals whose data may be collected, and anonymize or pseudonymize data when necessary.
  • Data Access Controls: Implement strict access controls to limit who can access the collected data, and restrict access to only authorized personnel.
  • Data Retention: Establish policies for data retention and deletion to ensure that data is not stored longer than necessary.
2. Security:
  • Cybersecurity: Implement robust cybersecurity measures to protect data from unauthorized access, data breaches, and cyberattacks. This includes encryption, firewalls, intrusion detection systems, and regular security audits.
  • Authentication and Authorization: Implement strong authentication mechanisms and role-based access control to ensure that only authorized users can access and manipulate data related to laboratory mapping.
  • Physical Security: Secure physical access to the laboratory and any hardware or equipment used for data collection or processing to prevent unauthorized physical access.
3. Data Integrity:
  • Data Validation: Implement data validation checks to ensure the integrity of the data collected. This includes error-checking mechanisms and data validation rules to identify and address data inconsistencies.
  • Audit Trails: Maintain audit trails to track changes made to the data, who made those changes, and when they were made. This helps ensure data integrity and accountability.
4. Compliance:
  • Regulatory Compliance: Ensure that the use of AI for laboratory mapping complies with relevant industry-specific regulations and standards (e.g., GLP, GMP) and any regional or national laws governing research and data privacy.
5. Ethical Considerations:
  • Ethical Use: Consider the ethical implications of using AI in laboratory mapping, including the potential for bias in AI algorithms and the responsible use of AI-generated insights.
6. Data Sharing:
  • Data Sharing Policies: If laboratory mapping data is intended to be shared with external parties, establish clear data sharing policies and procedures, including data anonymization and secure data transfer mechanisms.
7. Employee Training:
  • Security Awareness: Provide training and awareness programs for laboratory staff and AI practitioners to educate them about privacy and security best practices and their roles in maintaining data security.
8. Incident Response:
  • Incident Response Plan: Develop an incident response plan that outlines how to respond to data breaches or security incidents promptly, including notification procedures if sensitive data is compromised.
9. Vendor Security:
  • Third-Party Services: If using third-party AI solutions or services, assess the security measures they have in place to protect your data and ensure they comply with your organization's security standards.
Addressing these privacy and security considerations is critical to ensure the responsible and secure use of AI for laboratory mapping. It helps protect sensitive research data, maintain the integrity of research findings, and safeguard the privacy of individuals involved in the research process. Additionally, involving data privacy and cybersecurity experts in the planning and implementation of AI projects in laboratory settings is advisable to mitigate risks effectively.
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What is the system of food security in India and why nutrition security is more important than food security?
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Food security focuses on quantity of food which is important but limited in scope. It is essential to talk about nutrition security now as preventable diet-related diseases are on the rise. Diabetes and obesity rates continue to rise, especially among children. Food security is closely related to household resources, disposable income and socioeconomic status. It is also strongly interlinked with other issues, such as food prices, global environment change, water, and energy and agriculture growth. The agri-food systems are the most important part of the Indian economy. Food and nutritional security is the key to attain to the Sustainable Development Goals and other high-level aspirational goals. Food security does not exist without nutrition security. Unfortunately, many organizations and policies focused on quantity rather than quality of food over the past half-century. It's the difference between eating bread every day or a diverse diet incorporating all the food groups every day. Food security is defined as the availability and the access of food to all people; whereas nutrition security demands the intake of a wide range of foods which provides the essential needed nutrients. It is estimated that the average dietary intake in India is 2280 calories.Food and nutrition insecurity can increase the risk of type 2 diabetes and affect diabetes management. Millions of people across America have problems accessing enough food or enough healthy food known as food and nutrition insecurity. Although food security refers to access to a safe and sufficient food supply to meet dietary needs, nutrition security further warrants that individuals actually consume the food to which they have access and that appropriate nutrition education is available to foster positive food choice. Food insecurity, whether a relative change or absolute severity, may increase the risk of malnutrition in all of its forms. Certain groups of the population are more vulnerable to food insecurity and thus more susceptible to dietary inadequacies.
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While integrating manufacturing design, Industrial Revolution 4.0, and Lean Manufacturing can bring significant benefits but there are also challenges and problems that can arise in the process in term of Data Privacy and Security. How we can solve this problems?
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Thanks Martin McKie rtin for your suggestion paper. i will read your paper.
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what kind of securities are provided by the network providers and how much security does the common people received
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Here below the most common reasons of facing those data insecurities are presented:
The abundance of insecurities in protecting users' data in the internet world can be attributed to several complex factors:
  1. Evolution of Technology: The internet has evolved rapidly, and new technologies are constantly emerging. This fast pace of development often means that security measures are playing catch-up to new threats and vulnerabilities. As a result, legacy systems and technologies with inherent vulnerabilities might still be in use.
  2. Complexity: The internet is a complex ecosystem involving a multitude of devices, software, protocols, and services. Each layer adds its own potential vulnerabilities. The sheer complexity makes it difficult to predict and address all possible attack vectors.
  3. Profit Motive for Attackers: Cybercriminals are motivated by financial gain. With the rise of cybercrime-as-a-service and the ability to monetize stolen data, hackers are incentivized to find and exploit vulnerabilities for their own benefit.
  4. Human Factor: Many security breaches occur due to human error, such as weak passwords, falling for phishing attacks, or misconfigured settings. Education and awareness about cybersecurity are not yet at the level they should be.
  5. Lack of Standardization: The lack of standardized security practices across the internet contributes to inconsistencies in how data is protected. Different platforms and services might implement security measures differently or not at all.
  6. Resource Constraints: Not all organizations, especially smaller ones, have the resources or expertise to implement robust cybersecurity measures. This can create vulnerabilities that attackers can exploit.
  7. Rapid Development Cycles: Software and online services are often developed with short release cycles, leaving limited time for thorough security testing. This can result in products being released with undiscovered vulnerabilities.
  8. Legacy Systems: Many older systems were designed and built before security concerns were as prominent as they are today. These systems might not be easily updated or secured without significant overhauls.
  9. Third-Party Dependencies: Modern applications and services often rely on third-party libraries and components. If these components have vulnerabilities, they can be exploited to breach the security of the entire system.
  10. Global Nature of the Internet: The global nature of the internet means that laws, regulations, and security practices vary widely across jurisdictions. This can make it challenging to enforce consistent security standards.
  11. Rapidly Changing Threat Landscape: New attack techniques and vulnerabilities are constantly being discovered. This requires continuous vigilance and adaptation of security measures to stay ahead of potential threats.
Addressing these challenges requires a combination of technical solutions, education, regulations, and a shift in the overall mindset toward security. It's an ongoing battle that requires collaboration from all stakeholders, including governments, technology companies, security experts, and individual users.
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Currently, I am exploring federated learning (FL). FL seems going to be in trend soon because of its promising functionality. Please share your valuable opinion regarding the following concerns.
  • What are the current trends in FL?
  • What are the open challenges in FL?
  • What are the open security challenges in FL?
  • Which emerging technology can be a suitable candidate to merge with FL?
Thanks for your time.
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  1. Communication Efficiency: Federated learning involves frequent communication between devices and a central server. Optimizing communication protocols and reducing communication overhead is a challenge, especially for devices with limited bandwidth.
  2. Heterogeneous Data: Nodes in a federated learning system may have diverse and non-i.i.d (independent and identically distributed) data. Developing methods to handle data heterogeneity while preserving model performance is crucial.
  3. Model Aggregation: Combining models from different nodes without compromising model accuracy or privacy is complex. Aggregation methods need to be robust against outliers, adversarial nodes, and noisy updates.
  4. Privacy and Security: Ensuring that individual node data remains private is a central concern. New techniques for encryption, differential privacy, and secure aggregation are needed to protect sensitive information.
  5. Bias and Fairness: Federated learning can inherit biases present in node data, leading to biased models. Addressing bias and fairness issues across distributed data sources is a challenge.
  6. Imbalanced Data: Some nodes might have imbalanced datasets, leading to biased models. Developing techniques to mitigate the impact of data imbalance on model training is essential.
  7. Node Heterogeneity: Devices can have varying computation power and energy constraints. Designing federated algorithms that accommodate such heterogeneity is important for scalability and inclusivity.
  8. Stragglers: Slow or faulty nodes can slow down the training process. Techniques for dealing with stragglers and their impact on overall model performance need to be explored.
  9. Model Deployment: Transitioning federated models to production environments while maintaining security, performance, and compatibility with different devices is a challenge.
  10. Cross-Domain Learning: Extending federated learning to scenarios where nodes have different domains or tasks is an emerging area that requires novel solutions.
  11. Adversarial Attacks: Federated learning models could be vulnerable to new types of attacks, including those targeting the aggregation process or compromising the central server.
  12. Resource-efficient Algorithms: Developing algorithms that optimize for computation, memory, and energy usage while maintaining model accuracy is crucial for resource-constrained devices.
  13. Regulatory and Ethical Concerns: Ensuring compliance with data protection regulations and ethical considerations is essential in federated learning, particularly when dealing with personal or sensitive data.
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Nowdays, the machine learning techniques and deep learning techniques have been employed in tackling with various of kinds of security problems, such as malware mitigation. Is the difference of their performance obvious? Which is better?
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Yes, there are differences between machine-learning (ML) techniques and deep-learning (DL) techniques when employed to tackle security problems, although they share similarities as well. Here's an overview of their distinctions:
Machine Learning (ML) Techniques:
  1. Feature Engineering: ML often requires manual feature engineering, where relevant features need to be identified and extracted from data before training the model.
  2. Dimensionality: ML models might struggle with high-dimensional data, necessitating dimensionality reduction techniques.
  3. Performance: ML models may perform well for structured data and simpler tasks, but could struggle with complex patterns in unstructured data.
  4. Generalization: ML models might need fine-tuning for optimal generalization to new and unseen data.
  5. Interpretability: Some ML models offer better interpretability, making it easier to understand the decision-making process.
Deep Learning (DL) Techniques:
  1. Feature Learning: DL models can automatically learn relevant features from raw data, reducing the need for manual feature engineering.
  2. High Dimensionality: DL models handle high-dimensional data efficiently and can uncover intricate patterns.
  3. Complex Patterns: DL excels in capturing complex patterns in unstructured data, such as images, audio, and text.
  4. Data Abundance: DL models often require large amounts of labeled data to perform well, making them well-suited for well-labeled datasets.
  5. Black Box Nature: DL models can be considered more of a "black box" due to their complexity, making their decision-making less interpretable.
In the context of security problems:
  • ML in Security: ML techniques are effective for tasks like intrusion detection, malware classification, and spam filtering. They can identify known patterns of attacks or anomalies based on historical data.
  • DL in Security: DL techniques excel in tasks like image-based authentication, facial recognition, and natural language processing for threat analysis. Their ability to learn intricate patterns makes them suitable for complex, evolving threats.
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How do you think artificial intelligence can improve cybersecurity?
What are the risks and benefits?
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Yes, artificial intelligence (AI) can significantly improve cybersecurity in various ways:
  1. Threat Detection and Prevention: AI-powered systems can analyze vast amounts of data in real time to detect anomalies, patterns, and potential threats that may go unnoticed by traditional methods. Machine learning algorithms can learn from historical data to identify new and evolving threats.
  2. Behavioral Analysis: AI can analyze user and system behaviors to identify deviations from the norm, helping to detect insider threats and unusual activities that could indicate a cyberattack.
  3. Automated Incident Response: AI can automate responses to certain types of cyber threats, enabling faster and more effective mitigation of attacks. This reduces the manual effort required for incident response and accelerates the remediation process.
  4. Advanced Threat Intelligence: AI-driven threat intelligence platforms can gather and analyze information from various sources to provide organizations with up-to-date information about emerging threats and vulnerabilities.
  5. Malware Detection: AI algorithms can identify known and unknown malware by analyzing file attributes, behavior, and code patterns. This helps in real-time malware detection and prevention.
  6. User Authentication and Access Control: AI-powered authentication systems can use behavioral biometrics, device recognition, and contextual data to enhance user authentication and prevent unauthorized access.
  7. Phishing Detection: AI can identify phishing emails by analyzing content, sender behavior, and contextual information, reducing the risk of successful phishing attacks.
  8. Network Security: AI can monitor network traffic, identify unusual patterns, and detect potential intrusions or unauthorized activities.
  9. Vulnerability Management: AI can assess software code, scan for vulnerabilities, and suggest patches or remediation actions to improve system security.
  10. Adaptive Security: AI can dynamically adjust security measures based on real-time threats and vulnerabilities, ensuring a more responsive and adaptable defense system.
  11. Predictive Analytics: AI can predict potential future threats based on historical data, enabling organizations to proactively strengthen their defenses.
  12. Reducing False Positives: AI can help reduce the number of false positives generated by security systems, improving the accuracy of threat detection and reducing alert fatigue for security analysts.
  13. Security Analytics: AI can help security analysts make sense of large volumes of security data, providing insights that aid in decision-making and incident response.
  14. Cybersecurity Training: AI-powered simulations and training platforms can help educate employees about cybersecurity best practices, increasing their awareness of potential threats.
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Data Security Big Data
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Big Data needs to be secured for several important reasons:
  1. Confidentiality: Big Data often contains sensitive information, including personal, financial, and proprietary data. Ensuring its confidentiality is crucial to prevent unauthorized access and data breaches.
  2. Integrity: Data integrity ensures that the information remains accurate and unaltered. Securing Big Data helps prevent unauthorized modifications or tampering.
  3. Availability: Protecting Big Data ensures that it remains available to authorized users when needed, preventing disruptions that could lead to service outages or downtime.
  4. Privacy: Large datasets can include personal information that, if mishandled or breached, could lead to privacy violations and identity theft.
  5. Regulatory Compliance: Many industries and jurisdictions have regulations that mandate the security and protection of data, such as GDPR in Europe or HIPAA in healthcare. Non-compliance can lead to legal and financial consequences.
  6. Business Reputation: A data breach can significantly damage an organization's reputation and erode customer trust, leading to loss of business and revenue.
  7. Data Monetization: Organizations often use Big Data to gain insights and generate revenue. Securing this data is critical to protect their investment and competitive advantage.
  8. Competitive Advantage: Companies may use Big Data to analyze market trends, customer behaviors, and other insights that can give them a competitive edge. Securing this data safeguards their strategic advantage.
As for national security, yes, Big Data can pose potential threats:
  1. Cybersecurity: Large-scale data breaches and cyberattacks can target critical infrastructure, government systems, and sensitive information, jeopardizing national security.
  2. Espionage: Hostile actors, including foreign governments and hackers, can exploit vulnerabilities to steal classified information, intelligence, and strategic plans.
  3. Disinformation: Manipulating and spreading false information within Big Data can influence public opinion, political stability, and social harmony, impacting a nation's security.
  4. Crime Detection and Prevention: Securing Big Data is essential for law enforcement agencies to effectively analyze and respond to criminal activities and potential threats.
  5. Counterterrorism: Analyzing vast amounts of data can help identify patterns and trends related to terrorism and radicalization, aiding counterterrorism efforts.
  6. Geopolitical Intelligence: Analyzing data can provide insights into global events, potential conflicts, and emerging threats that affect a nation's security interests.
  7. Border Security: Big Data analytics can enhance border security by analyzing travel patterns, identifying potential threats, and managing immigration and customs processes.
securing Big Data is crucial to protect individuals' privacy, organizations' interests, and national security. The potential for data breaches, cyberattacks, and misuse of data underscores the importance of robust security measures and practices.
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We have successfully implemented several solar projects with a combined capacity of around 2 MW. Furthermore, we are in the process of devising plans for additional installations of solar and renewable energy projects. However, we are uncertain about the avenues available for securing international financial assistance for projects located within Iraq, such as through the utilization of carbon credits. If anyone possesses knowledge or can offer guidance in this regard, we would greatly appreciate the support.
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Hello mr you can use PV syst software it include carbone balance also financial analysis also cash flow and yearly net profit of Solar projects
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Udawalawa is a large reservoir constructed in 1960s, mainly for the purpose of irrigation. Later, around 1990s, hydropower reservoir was constructed at the upstream of the same catchment intercepting a large portion of inflows to Udawalawe. Now, due to prevailing drought, Udawalawa farmers are facing severe shortage of water for their ongoing rice cultivation. Electrical authorities are refusing to release water from the upstream reservoir and trying to secure the uninterrupted power production. What are the laws and regulations, national or international, available to tackle this situation and secure water rites of farmers.
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Laws and regulations related to riparian rights of water in river systems and the priority order of water-using activities vary significantly from one jurisdiction to another. These laws are typically established at the national, regional, or local levels, depending on the legal and administrative framework of each country or state. Here are some general concepts and examples of laws that may apply:
  1. Riparian Rights Laws: Riparian rights are legal rights that pertain to landowners who have property adjacent to a water body (such as a river or stream). These rights typically include the right to reasonable use of the water for domestic, agricultural, and industrial purposes. Riparian rights laws often outline principles related to: Reasonable Use Doctrine: Landowners are entitled to reasonable use of water resources, but this use cannot unreasonably interfere with the rights of other riparian landowners. No Harm Principle: Riparian landowners cannot use the water in a way that harms downstream or neighboring landowners. Prior Appropriation Doctrine: In some regions, a prior appropriation system may be used, where the first user of water gains a priority right, irrespective of riparian ownership.
  2. Water Allocation and Priority Laws: Many jurisdictions have laws that prioritize certain water uses over others, especially in times of water scarcity. These laws often establish a priority order for water allocation based on the importance of the water use. Priorities may be assigned to activities such as: Domestic Use: Water for households, drinking, sanitation, and basic human needs. Agriculture: Irrigation for crops and livestock. Industry and Commerce: Water for manufacturing, energy production, and other commercial activities. Environmental Flows: Ensuring that sufficient water is left in the river to support ecological health and the needs of aquatic ecosystems. Recreation and Aesthetic Uses: Boating, fishing, and other recreational activities.
  3. Water Management Agencies and Authorities: Many countries have established government agencies or authorities responsible for managing water resources, including the allocation of water rights, monitoring water use, and enforcing regulations. These agencies play a critical role in ensuring that water use is equitable and sustainable.
  4. Water Use Permits and Licenses: In some regions, individuals or entities seeking to use water resources must obtain permits or licenses from the relevant water management authority. These permits may specify the amount of water that can be used, the purpose of use, and any conditions or restrictions.
  5. International Agreements: For rivers that flow across international borders, there may be treaties or agreements between countries governing the allocation and use of water resources. These agreements aim to ensure equitable sharing of water and prevent conflicts.
It's important to note that the specifics of these laws and regulations can vary widely based on legal traditions, cultural norms, water availability, and other factors. If you are seeking information about riparian rights and water allocation in a specific jurisdiction, it's recommended to consult local legal experts, government agencies, or official resources to understand the precise legal framework that applies.
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How is user data handled and secured within ChatGPT to ensure privacy and prevent breaches?
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I assume there would be special areas of AI related to military, national security, and alike info, that will need a special access credentials. Other than that, the AI should be wide open. Pretty much similar to Wikipedia.
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How can blockchain technology best help securing identity data and how blockchain can help security of the information security triad?
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Dr Haroon Rashid Hammood Al-Dallal thank you for your contribution to the discussion
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Yes, hacking a vehicle and causing an accident through internet technology is theoretically possible, although it's important to note that modern vehicles have multiple layers of security measures in place to prevent such events and ensure the safety of passengers.
Modern vehicles are equipped with various electronic control units (ECUs) that manage different systems, such as engine control, brakes, steering, and more. These ECUs are connected through a Controller Area Network (CAN) bus, which allows them to communicate and share information. If a hacker gains unauthorized access to a vehicle's CAN bus through internet technology, they might potentially manipulate the vehicle's systems and cause a malfunction that could lead to an accident.
However, the reality is more complex:
  1. Security Measures: Vehicle manufacturers implement robust security measures to prevent unauthorized access and hacking. These include encryption, secure coding practices, intrusion detection systems, and more.
  2. Physical Controls: Many critical vehicle systems, such as brakes and steering, are designed with redundant physical controls that can override electronic commands. This makes it difficult for hackers to completely take control of a vehicle remotely.
  3. Ethical and Legal Constraints: Hacking a vehicle and causing harm is illegal and unethical. Anyone attempting such actions could face serious legal consequences.
  4. Rapid Response: In the event of unusual or malicious activity, vehicles often have mechanisms that trigger warnings and alerts to the driver, and manufacturers can remotely update or patch software to address vulnerabilities.
  5. Complexity: Hacking a vehicle's systems requires a deep understanding of its architecture and software. While researchers and hackers have demonstrated vulnerabilities in the past, it's not a simple task to carry out successfully.
  6. Public Awareness: As hacking risks have become more widely known, both vehicle manufacturers and the public are more vigilant about potential threats, which contributes to the implementation of stronger security measures.
It's crucial for vehicle manufacturers to continue improving security measures and staying ahead of potential threats. If you have concerns about vehicle security or hacking vulnerabilities, it's best to consult with experts in the field or contact the vehicle manufacturer for information on the security features and measures they have implemented.
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Here are some of my research presentations discussing seriousness of the issue.
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Which authentication schemes would perform better than improved Feige–Fiat–Shamir (IFFS) for modeling a secure IoT-integrated WBAN framework for e-healthcare?
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Dear Opeyemi A. Ajibola,
You may want to look over the following data:
An improved parallel interactive Feige-Fiat-Shamir identification scheme with almost zero soundness error and complete zero-knowledge
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Fiat-Shamir and Correlation Intractability from Strong KDM-Secure Encryption
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Feige-Fiat-Shamir and Zero Knowledge Proof
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Do we need Central cooling by CFC and Renewable Energy in an open-door and more secure cooling system?
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There are some chemical reactions that absorb heat from air when interacting. Researchers should make a patent for renewable air conditioning from them.
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I am currently working on my master's thesis in the field of security, focusing on detecting malware in server environments.
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There are several sources where you can find server log datasets, depending on your specific requirements. Here are a few options:
Kaggle: Kaggle is a popular platform for finding datasets. You can search for "server logs" on Kaggle and find several datasets, such as "Web Server Log Data," "Apache Access Logs," and "Nginx Access Logs."
Loghub: Loghub is a repository of publicly available log datasets. You can search for "server logs" on Loghub and find several datasets, such as "Web Server Access Logs" and "OpenStack Nova Compute Logs."
AWS Public Datasets: AWS Public Datasets is a collection of large, public datasets hosted on AWS. You can search for "server logs" on AWS Public Datasets and find several datasets, such as "Web Server Access Logs" and "AWS CloudTrail Logs."
ELK Stack: The ELK Stack (Elasticsearch, Logstash, and Kibana) is a popular open-source tool for log analysis. You can install an ELK Stack on your own server and generate your own log data for analysis.
Your own servers: If you have your own servers, you can generate your own log data for analysis. Most servers will have log files that you can access and analyze.
It's important to note that server logs can contain sensitive information, so be sure to check the license and terms of use before using any dataset. Additionally, anonymize any personal information before using the data.
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What are the steps that can be taken to avoid privacy related issues?
How much personal data is safe on online social networking sites?
How to solve these privacy and security issues?
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اتباع القوانين والتعليمات الخاصة بحفظ حقوق الملكية الفكرية
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Unethical business practices operate in different countries to varying degrees and participate in economic processes.
For many entities, market participants, business partners and consumers, they generate additional costs.
They can also be a source of gray economy growth, including avoiding paying taxes.
Thus, there are social costs for individual entities and financial for the entire economy.
On the capital markets, one of unethical business practices is, for example, insider trading, ie the use of confidential information by decision-makers with access to confidential information used to conduct transactions to purchase or sell financial instruments, including securities or other securities or other capital markets.
In individual countries, there are various instruments to combat the use of unethical business practices, the shadow economy, etc.
The effectiveness of individual normative solutions, the scale of restrictions applied, and the business mentality of market participants, entrepreneurs and businessmen are different.
Another mentality is related to the level of awareness regarding corporate social responsibility.
In individual countries, social campaigns are carried out suggesting the legitimacy of developing concepts based on corporate social responsibility.
In view of the above, please answer the following question: Is unethical business practices a negative external effect of non-ideal market structures or imperfection of the social market economy?
Please, answer, comments. I invite you to the discussion.
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Imperfections of the social market economy as unethical business practices do reflect human behavior, i.e. not external to market structures as the market should not be idealized as perfect answer to satisfy human needs.
As the old police officer saying at shift change goes: be careful out there !
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Authors are solicited to contribute to the book series by submitting articles that illustrate research results, projects, surveying works and industrial experiences that describe significant advances in the following areas related to IoT, but are not limited to
  1. IoT Communication Technologies
  2. IoT Architectures & Platforms
  3. IoT Performance & Management
  4. IoT Privacy & Security
  5. IoT Embedded Systems, Sensors, Actuators
  6. Practical and Innovative Applications of IoT & IoT Networks (smart cities, smart mobility, smart home, smart health, smart grid, etc.)
  7. IoT for the industry and Business
  8. IoT operations & Interoperability
  9. Augmented Reality and virtual reality
  10. IoT & Artificial intelligence
go to www.iipseries.org for submission.
last date for submission is 31 july, 2023
Book Series Id: IIPV3EBS08_G2
kindly enter my reference id: IIPER1673412413 while submitting the chapter.
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Dear Anatol,
You can submit in the book series, using my reference id that is mentioned. We will check & revert you
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Discuss the constraints and challenges faced in implementing millet-based integrated farming systems for food and nutritional security.
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Implementing millet-based integrated farming systems for food and nutritional security faces several constraints and challenges. Here are some key ones:
  1. Limited awareness and knowledge: One of the primary challenges is the limited awareness and knowledge about millet-based integrated farming systems among farmers, policymakers, and consumers. Millets have been traditionally considered minor crops, and their potential for food and nutritional security is often underestimated. Creating awareness and disseminating knowledge about the benefits and techniques of integrated farming systems is crucial.
  2. Lack of infrastructure and resources: Implementing integrated farming systems requires adequate infrastructure, including storage facilities, processing units, and market linkages. In many regions, especially in rural areas, the lack of such infrastructure poses a significant constraint. Additionally, farmers may face challenges in accessing quality seeds, fertilizers, and agricultural machinery necessary for integrated farming.
  3. Climate change and variability: Millets are generally more resilient to climate change and require less water compared to other crops. However, climate change and variability can still impact millet production and integrated farming systems. Erratic rainfall patterns, droughts, floods, and extreme temperatures can affect crop yields and livestock rearing, leading to food and nutritional insecurity. Adapting integrated farming systems to climate change becomes crucial to mitigate these risks.
  4. Market and value chain limitations: The lack of well-established and organized markets for millet-based products can hinder the adoption of integrated farming systems. Insufficient market linkages, price fluctuations, and low consumer demand for millet products may discourage farmers from investing in these systems. Strengthening market infrastructure and creating demand for millet-based products are essential to make integrated farming economically viable.
  5. Policy and institutional support: Adequate policy and institutional support are necessary to promote millet-based integrated farming systems. This includes supportive policies, incentives, subsidies for farmers, research and development initiatives, capacity-building programs, and effective extension services. The lack of appropriate policies and institutional mechanisms can be a major constraint in scaling up these systems.
  6. Socio-cultural factors: Millets have lost popularity over the years due to various socio-cultural factors. Changing dietary preferences, urbanization, and the perception of millet as "poor people's food" have contributed to the decline in millet consumption. Overcoming these sociocultural barriers and promoting millets as nutritious and sustainable food options require targeted awareness campaigns and behavior change interventions.
  7. Land tenure and farm size: In some regions, limited land availability and small farm sizes can pose challenges to implementing integrated farming systems. Lack of sufficient land may restrict the integration of crops, livestock, and other components, limiting the system's potential benefits challenge. Addressing land tenure issues and exploring alternative models like cooperative farming can help overcome these constraints.
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We wish to invite members of the public to submit certain types of videos for a research project. The videos are likely to be too large for people to be able to email to us. Has anyone found a good solution? Any online submission area would need to be secure such that only the researcher could see the submitted videos, for ethical reasons.
Ideally it would also allow each person to submit a caption with their video, and/or it would be free!
Thanks, Charlotte
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Hi Charlotte. Have you considered WeTransfer for this? If you get a premium account they should be able to send large videos to you or folders or videos and they can also add a comment at the same time. It should also be private only to you.
Best wishes, Kris
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Abstract MANET is a wireless network that lacks infrastructural support. Most operations they perform are coordinated between nodes because of their limited transmission range. Assess the secure MANET routing protocol in a malicious environment. However, in the MANET environment security is an important constraint that affects the data transmission rate and cause data loss. This paper developed an Intrusion Detection System Conditional RandomField (IDS – CRF) model for security. The developed model uses the hashing function integrated with the Conditional Random Field model. The IDS – CRF model uses the label sequences for data security in the MANET environment. The model uses the DSR protocol with the discriminative field to process the secure data in the MANET. The proposed IDS-CRF model uses the hashing function for improved data transmission security in the MANET environment. The performance of the proposed IDS – CRF model is comparatively examined with the conventional DSR protocol. The comparative analysis expressed that the proposed IDS – CRF model achieves the ~4% reduction in the delay and ~2% reduction in the routing overhead. Similarly, the proposed IDS – CRF model achieves the ~4% reduced energy consumption. In terms of the Packet delivery ratio and throughput the proposed IDS – CRF model achieves the ~4% - ~6% improved performance than DSR model.
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Technology and the economy are deeply interconnected, and advancements in technology have had a significant impact on the economic sector, and vice versa. The relationship between technology and the economy can be viewed from several perspectives:
Innovation and Technology Adoption: Technological advancements have enabled the creation of new products and services, and businesses that innovate and adopt new technologies can gain a competitive advantage over their peers. The adoption of new technology can also lead to increased productivity, cost savings, and improved customer experiences, all of which can positively impact the economic sector.
Automation and Job Disruption: The adoption of new technologies can also lead to job displacement, particularly in industries that rely heavily on manual labor. However, the automation of certain tasks can also lead to the creation of new jobs in the technology sector. Additionally, the increased efficiency and productivity resulting from automation can lead to economic growth and increased job opportunities in other sectors.
Data Analytics and Decision Making: The use of data analytics and artificial intelligence in business decision making has become increasingly prevalent, as companies seek to gain insights into consumer behavior and improve operational efficiency. These technologies can provide businesses with a competitive advantage by enabling them to make data-driven decisions and improve their bottom line.
E-commerce and Globalization: The growth of e-commerce has enabled businesses to expand their customer base globally, leading to increased trade and economic growth. Additionally, the rise of digital platforms has enabled small businesses to compete with larger firms and enter new markets.
Overall, technology and the economy are closely intertwined, and advancements in technology have the potential to shape the future of the economic sector in significant ways. However, the impact of technology on the economic sector is not always positive, and policymakers must consider the potential impact of new technologies on the workforce and society as a whole.
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Challenges confronting CISOs are evolving beyond technology, cybersecurity, and controls, as Gartner predictions for 2023 reveal. “By 2025, lack of talent or human failure will be responsible for over half of significant cyber incidents."
How can modern cybersecurity leaders strengthen their programs in the face of these challenges?
“By 2025, the consumerization of AI-enabled fraud will fundamentally change enterprise attack surface driving more outsourcing of enterprise trust and focus on security education and awareness.”
We believe, in this report you will learn key findings, market implications, and recommendations on:
  • Designing a cybersecurity program that leverages data to improve decision making
  • Demonstrating how a strong security performance is relevant to winning business
  • Integrating cybersecurity into the overall business with shareable results
  • Effectively allocating budget to both technology and education to establish program consistency
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Since it's assumed that P != NP, cyberspace is safe according to SSL protocol.
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The first 5G radio networks are now live. This generation of telecommunication system aims to deliver
  • Enhanced mobile broadband,
  • Massive machine-type communications,
  • Ultra-reliable and low latency communications.
The purpose is to be faster, more reliable and manage the scale of devices predicted for the Mobile Internet of Things (MIoT). Enabling the digital transformation of our society, business processes and manufacturing. To enable this, 5G will deliver multi-network slicing, multi-level of services and multi-connectivity network capabilities. To allow the required flexibility, agility and economies of scale these technologies will be delivered via virtual and containerised environments. This is a revolutionary way of working for the industry. 5G has designed in security controls to address many of the threats faced in today’s 4G/3G/2G networks. These controls include new mutual authentication capabilities, enhanced subscriber identity protection, and additional security mechanisms. 5G offers the mobile industry an unprecedented opportunity to uplift network and service security levels. 5G provides preventative measures to limit the impact to known threats, but the adoption of new network technologies introduces potential new threats for the industry to manage.
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The security of data transmitted via the ubiquitous 5G communication network infrastructure is a paramount concern. While 5G offers incredible speed, low latency, and increased capacity, it also presents new security challenges. The sheer volume of data flowing through the network increases the attack surface and makes it more attractive to cybercriminals. However, efforts have been made to enhance security in 5G, including stronger encryption, improved authentication protocols, and network slicing to isolate different types of traffic. Additionally, advanced technologies like artificial intelligence and machine learning can be employed to detect and mitigate potential threats. Nonetheless, as with any communication network, achieving absolute security is a complex task that requires ongoing collaboration between industry, government, and cybersecurity experts to ensure the protection of user and cloud data in the era of ubiquitous 5G.
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A Chaotic-Based Encryption/Decryption for Secure Communications
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Certainly! Here's a brief explanation of the Henon map image encryption algorithm. The Henon map is a two-dimensional discrete dynamical system that exhibits chaotic behavior. To encrypt an image using this algorithm, first, convert the image into a grayscale format. Then, apply the Henon map equations to each pixel of the image iteratively. The Henon map equations are defined as follows: x_n+1 = y_n + 1 - a * x_n^2, and y_n+1 = b * x_n. Here, 'a' and 'b' are the parameters that determine the chaotic behavior of the map. Choose appropriate values for these parameters. For encryption, use the initial conditions (x_0, y_0) as the secret key. Iterate the Henon map equations for a specific number of iterations, and use the resulting (x_n, y_n) values as the encryption key. XOR the grayscale pixel values with the encryption key to encrypt the image. For decryption, generate the same encryption key using the initial conditions, and XOR the encrypted pixel values with the key to obtain the original image. Implementing this algorithm in MATLAB or Python involves defining functions for the Henon map equations, reading and processing the image, and performing the encryption and decryption steps using loops or vectorized operations.
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I am attempting to show the significance of the Risk Management Framework to securing SMEs in Jamaica. Special focus is being placed on ISO 27001
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ISO 27001, an international standard for information security management, holds great applicability in securing SMEs (Small and Medium Enterprises). Implementing ISO 27001 provides a systematic and comprehensive framework for identifying, assessing, and managing risks associated with information security. By adopting this standard, SMEs in Jamaica can establish robust security controls, protect sensitive data, ensure compliance with regulations, and build trust with their customers and partners. ISO 27001's risk management approach helps SMEs prioritize their security investments and make informed decisions to mitigate potential threats, enhancing their overall security posture and resilience in an increasingly digital landscape.
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This question explores the role of the consensus mechanism in ensuring the security of blockchain networks, discussing concepts such as proof-of-work, proof-of-stake, and their impact on network security.
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FAKE ANSWER WARNING
The answer by
Rana Hamza Shakil
was analysed by https://gptzero.me, and the result was
Your text is likely to be written entirely by AI
This person uses ChatGPT to answer questions without apparently knowing or caring whether they are right or wrong.
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The question revolves around exploring the potential benefits of integrating blockchain technology into cloud computing environments, specifically focusing on enhancing security and trustworthiness of data storage and transactions.
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Integrating blockchain technology into cloud computing environments can significantly enhance the security and trustworthiness of data storage and transactions. By leveraging blockchain's decentralized and immutable nature, sensitive data can be securely stored and accessed through encrypted blocks distributed across multiple nodes, reducing the risk of single points of failure or unauthorized access. The use of smart contracts within blockchain enables automated and verifiable execution of transactions, ensuring transparency and reducing the need for intermediaries. Additionally, blockchain's consensus mechanisms provide a robust and tamper-proof validation process for data integrity, increasing trust in the cloud computing environment. Overall, blockchain technology offers a promising solution to address security and trust concerns in cloud computing, empowering users with greater control and confidence over their data and transactions.
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This question aims to highlight the fundamental distinctions between traditional cybersecurity approaches, which often rely on centralized control and trusted third
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Traditional cybersecurity approaches and blockchain-based security differ in several key aspects. Here are the main differences between the two:
1. Centralized vs. Decentralized: Traditional cybersecurity relies on centralized systems, where security measures are implemented and managed by a central authority or organization. In contrast, blockchain-based security operates on a decentralized network of computers (nodes) that collectively validate and secure transactions and data.
2. Trust Model: Traditional cybersecurity approaches typically require trust in centralized authorities, such as governments or institutions, to maintain security. Blockchain-based security, on the other hand, employs a trustless model, where trust is distributed across the network through consensus algorithms. This eliminates the need for a central authority and allows participants to interact directly with each other.
3. Data Integrity: Traditional cybersecurity primarily focuses on securing data through encryption, access controls, firewalls, and other conventional measures. Blockchain-based security utilizes cryptographic techniques to ensure data integrity. Data stored on a blockchain is tamper-evident, as each block contains a cryptographic hash of the previous block, making it extremely difficult to modify historical data without detection.
4. Immutable Records: Blockchain technology provides an immutable and transparent ledger that records all transactions and data modifications. Once a transaction or data entry is recorded on the blockchain, it cannot be altered or deleted, creating a reliable and auditable trail of activities. This feature enhances transparency and reduces the risk of data manipulation.
5. Smart Contracts: One of the unique aspects of blockchain-based security is the use of smart contracts. Smart contracts are self-executing contracts with predefined rules encoded on the blockchain. They automatically execute transactions and enforce agreements when specific conditions are met. Smart contracts enhance security by reducing the need for intermediaries, minimizing human error, and ensuring that transactions occur as intended.
6. Resilience to Attacks: Traditional cybersecurity measures are susceptible to various types of attacks, such as DDoS attacks, data breaches, and ransomware. Blockchain-based security, due to its decentralized nature and consensus mechanisms, offers enhanced resilience against these attacks. An attacker would need to compromise a majority of the network's computing power to alter the blockchain's data, making it highly challenging and computationally expensive.
7. Privacy and Anonymity: Traditional cybersecurity often involves the collection and storage of personal data, which can raise privacy concerns. Blockchain-based security offers the potential for improved privacy and anonymity through techniques such as zero-knowledge proofs and private or permissioned blockchains. These techniques allow users to prove the validity of information without revealing the underlying data, enhancing privacy while still maintaining security.
It's worth noting that while blockchain-based security has unique advantages, it is not a one-size-fits-all solution. The technology has its own limitations and may not be suitable for all cybersecurity use cases. Evaluating the specific requirements and context is crucial when considering the adoption of blockchain-based security.
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This research question focuses on the specific domain of cybersecurity, namely the Internet of Things (IoT). IoT devices are becoming increasingly prevalent in various sectors, including healthcare, transportation, and smart homes, but they also pose unique security risks. Investigating the emerging threats and challenges associated with securing IoT devices and networks can provide valuable insights into the vulnerabilities and potential countermeasures needed to protect these interconnected systems. This research inquiry can contribute to the development of robust security frameworks, protocols, and strategies for IoT deployments, ultimately enhancing the overall cybersecurity landscape.
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The emerging threats and challenges in securing Internet of Things (IoT) devices and networks revolve around the increasing complexity and scale of interconnected devices. As IoT adoption grows, the expanding attack surface provides opportunities for cybercriminals to exploit vulnerabilities, compromising the privacy, integrity, and availability of devices and networks. Common challenges include weak device authentication and authorization mechanisms, inadequate encryption and data protection practices, lack of timely security updates and patch management, and the absence of standardized security protocols across different IoT platforms. Additionally, the proliferation of heterogeneous IoT ecosystems exacerbates interoperability issues and complicates security management. Addressing these challenges requires a holistic approach, incorporating robust security measures at every stage of the IoT lifecycle, fostering collaboration among stakeholders to establish industry standards, promoting security awareness among consumers and manufacturers, and investing in research and development for innovative security technologies.
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Hello everyone,
I'm currently using veins Inet project to simulate a vanet and its security attacks. I want to find the documentation of some of the veins modules like In the inet framework but I can't. Any help?
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Nihal Sanil i meant documentation for veins built in modules
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,,
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Dear doctor
"How Hadoop achieve Security?
1. Kerberos
Kerberos is an authentication protocol that is now used as a standard to implement authentication in the Hadoop cluster.
Hadoop, by default, does not do any authentication, which can have severe effects on the corporate data centers. To overcome this limitation, Kerberos which provides a secure way to authenticate users was introduced in the Hadoop Ecosystem.
Kerberos is the network authentication protocol developed at MIT, which uses “tickets” to allow nodes to identify themselves.
Hadoop uses the Kerberos protocol to ensure that someone who is making the request is the one who he claims to be.
In the secure mode, all Hadoop nodes use Kerberos to do mutual authentication. It means that when two nodes talk to each other, they each make sure that the other node is who it says it is.
Kerberos uses secret-key cryptography for providing authentication for client-server applications.
Kerberos in Hadoop
The client makes the three steps while using Hadoop with Kerberos.
  1. Authentication: In Kerberos, the client first authenticates itself to the authentication server. The authentication server provides the timestamped Ticket-Granting Ticket (TGT) to the client.
  2. Authorization: The client then uses TGT to request a service ticket from the Ticket-Granting Server.
  3. Service Request: On receiving the service ticket, the client directly interacts with the Hadoop cluster daemons such as NameNode and ResourceManager.
Authentication server and Ticket Granting Server together form the Key Distribution Center (KDC) of Kerberos.
The client on the user’s behalf performs the authorization and the service request steps.
The authentication step is carried out by the user through the kinit command, which will ask for a password.
We don’t need to enter a password every time while running a job because Ticket-Granting Ticket lasts for 10 hours by default, which is renewable up to a week.
If we don’t want ourselves to get a prompt for the password, we can create a Kerberos keytab file using ktutil command.
The keytab file stores passwords supplied to knit with the -t option.
2. Transparent Encryption in HDFS
For data protection, Hadoop HDFS implements transparent encryption. Once it is configured, the data that is to be read from and written to the special HDFS directories is encrypted and decrypted transparently without requiring any changes to the user application code.
This encryption is end-to-end encryption, which means that only the client will encrypt or decrypt the data. Hadoop HDFS will never store or have access to unencrypted data or unencrypted data encryption keys, satisfying at-rest encryption, and in-transit encryption.
At-rest encryption refers to the encryption of data when data is on persistent media such as a disk.
In-transit encryption means encryption of data when data is traveling over the network.
HDFS encryption enables the existing Hadoop applications to run transparently on the encrypted data.
This HDFS-level encryption also prevents the filesystem or OS-level attacks.
Architecture Design
Encryption Zone(EZ): It is a special directory whose content upon write is encrypted transparently, and during read, the content is transparently decrypted.
Encryption Zone Key (EZK): Every Encryption Zone key has a EZK specified during zone creation.
Data Encryption Key (DEK): Every file in EZ has its own unique DEK, which is never handled directly by HDFS. They are used to encrypt and decrypt the file data.
Encrypted Data Encryption Key(EDEK): HDFS handles EDEK. The client decrypts the EDEK and then uses the corresponding DEK to read/write data.
Key Management Server(KMS): The KMS is responsible for providing access to the stored EZK, generating new EDEK for storage on NameNode, and decrypting the EDEK for use by the HDFS clients.
The transparent encryption in HDFS works in the following manner:
  1. While creating a new file in EZ, the NameNode asks Key Management Server (KMS) to create a new Encrypted Data Encryption Key encrypted with EZk.
  2. This EDEK is stored on the NameNode as part of the file’s metadata.
  3. During file read within the encryption zone, NameNode provides the file’s EDEK along with the EZK version used to encrypt the EDEK to the client.
  4. The client then asks KMS to decrypt the EDEK. KMS first checks whether the client has permission to access the encryption zone key version or not. If the client has access permission, it uses the DEK to decrypt the file’s content.
All these steps take place automatically through the Hadoop HDFS client, the NameNode, and the KMS interactions.
3. HDFS file and directory permission
For authorizing the user, the Hadoop HDFS checks the files and directory permission after the user authentication.
The HDFS permission model is very similar to the POSIX model. Every file and directory in HDFS is having an owner and a group.
The files or directories have different permissions for the owner, group members, and all other users.
For files, r is for reading permission, w is for write or append permission.
For directories, r is the permission to list the content of the directory, w is the permission to create or delete files/directories, and x is the permission to access a child of the directory.
To restrict others except for the files/directory owner and the superuser, from deleting or moving the files within the directory, we can add a sticky bit on directories.
The owner of the file/directory is the user identity of the client process, and the group of file/directory is the parent directory group.
Also, every client process which is going to access the HDFS has a two-part identity that is a user name and group list.
The HDFS do a permission check for the file or directory accessed by the client as follow:
  1. If the user name of the client access process matches the owner of file or directory, then HDFS perform the test for the owner permissions;
  2. If the group of file/directory matches any of member of the group list of the client access process, then HDFS perform the test for the group permissions;
  3. Otherwise, the HDFS tests the other permissions of files/directories.
If the permissions check fails, then the client operation fails.
Wait!! Before start working on Hadoop do explore 15 Must-Know Hadoop Ecosystem Components.
Tools for Hadoop Security
The Hadoop ecosystem contains some tools for supporting Hadoop Security. The two major Apache open-source projects that support Hadoop Security are Knox and Ranger.
1. Knox
Knox is a REST API base perimeter security gateway that performs authentication, support monitoring, auditing, authorization management, and policy enforcement on Hadoop clusters. It authenticates user credentials generally against LDAP and Active Directory. It allows only the successfully authenticated users to access the Hadoop cluster.
2. Ranger
It is an authorization system that provides or denies access to Hadoop cluster resources such as HDFS files, Hive tables, etc. based on predefined policies. User request assumes to be already authenticated while coming to Ranger. It has different authorization functionality for different Hadoop components such as YARN, Hive, HBase, etc."
Dr.Sundus Fadhil Hantoosh
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AI ADVANCEMENTS SAVE THE DAY
With AI being used across all market areas, this technology, together with machine learning, has resulted in significant improvements in cybersecurity. In the development of automated security devices, natural language, facial identification, and autonomous advanced threat, AI has played a critical role.
It is also being used to create smart ransomware and assaults in order to get around the most up-to-date data security mechanisms. Threat detection systems using AI can forecast new assaults and immediately inform administrators of any data breaches. At last, AI advanced innovations are going to save the day.
These are all the top 5 trends that we are going to come across in the future. Change is always for the best. I hope the latest inventions in ethical hacking will resolve all the issues and provide better security.
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Cloud Computing, Big Data, IoT
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A mechanism to defend attacks based on the Training Data might be of interest. You might find the article below relevant, and it has some interesting references you might want to contact.
This is a very hot topic right now.
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Physical security
Network security
Software security
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You might find the article below relevant, and it has some interesting references you might want to contact.
This is a very hot topic right now.
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These days VAS are playing important roles in mobile networks, so without their security nobody can rely on them. In these instances cryptography plays an important role in securing these issues. I want to know the best way to apply cryptography VAS. Also any references would be appreciated.
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There are various ways in which cryptography can be applied to value-added services in mobile networks. One way is to use encryption to secure the communication between the mobile device and the service provider. This can be done by using algorithms such as AES (Advanced Encryption Standard) or RSA (Rivest–Shamir–Adleman).
Another way is to use digital signatures to authenticate users and transactions. Digital signatures use a combination of public and private keys to prove the authenticity of a message or transaction. This can be particularly important for financial transactions or other sensitive transactions.
Finally, it's important to use secure protocols such as TLS (Transport Layer Security) or HTTPS (HTTP Secure) to ensure that all communication between the mobile device and the service provider is encrypted and secure. These protocols can help to prevent eavesdropping and other types of attacks that can compromise the security of value-added services in mobile networks.
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The U.S. Department of Commerce’s National Institute of Standards and Technology (NIST) has chosen the first group of encryption tools that are designed to withstand the assault of a future quantum computer, which could potentially crack the security used to protect privacy in the digital systems we rely on every day — such as online banking and email software. The four selected encryption algorithms will become part of NIST’s post-quantum cryptographic standard, expected to be finalized in about two years.
Quantum computers are expected to be capable of breaking existing cryptographic algorithms, threatening the security of our data. The aim of post-quantum cryptography is to address this issue, devising new ways of protecting data and communications against the threat posed by super powerful quantum computers.
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To make modern cryptography standards unbreakable, several mathematical and software tools are employed. Some of the best mathematical tools include:
1. Asymmetric Encryption Algorithms: RSA and Elliptic Curve Cryptography (ECC) are widely used asymmetric encryption algorithms. ECC offers strong security with smaller key sizes compared to RSA.
2. Symmetric Encryption Algorithms: Advanced Encryption Standard (AES) is a symmetric encryption algorithm that is widely regarded as secure. AES is used for bulk data encryption.
Regarding software tools, the following are commonly used:
1. OpenSSL: An open-source software library that provides cryptographic functions and protocols. It supports a wide range of cryptographic algorithms and is widely adopted.
2. GnuPG (GNU Privacy Guard): An open-source implementation of the OpenPGP standard for email encryption and signing. It provides secure communication and data integrity.
3. Cryptlib: A powerful and portable software library that offers a comprehensive set of cryptographic functionalities, including encryption, digital signatures, and key management.
However, achieving unbreakable cryptography faces several challenges:
1. Quantum Computing: The development of powerful quantum computers poses a threat to existing public-key cryptographic algorithms, such as RSA and ECC. Quantum-resistant or post-quantum cryptography is an ongoing research area to address this challenge.
2. Implementation Vulnerabilities: Cryptographic algorithms may be secure in theory but can be compromised due to implementation flaws, side-channel attacks, or software bugs. Careful implementation and thorough security testing are crucial.
3. Key Management: Ensuring secure key generation, storage, distribution, and revocation is a critical challenge. Weaknesses in key management can undermine the overall security of a cryptographic system.
4. Social Engineering and Human Factors: Attackers often exploit human vulnerabilities through phishing, social engineering, or coercion to gain access to encryption keys or sensitive information.
Addressing these challenges requires continuous research, collaboration, and adherence to best practices in cryptography and security engineering.
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I am currently studying safe control of power systems and I am interested in finding out whether the security region constraints of power systems can be approximated by a set of linear constraints. The security region is defined as the set of all feasible operating points that satisfy the power balance and the thermal limits of the transmission lines. Linearizing the security region constraints can simplify the optimization and control problems of power systems, but it may also introduce errors and conservatism. I would like to know if there are any existing methods or results that can provide some insights or guidance on how to approximate the security region constraints by linear constraints. Any references or suggestions would be greatly appreciated.
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The security region constraints of power systems cannot be approximated by a set of linear constraints in a general sense. The operational constraints of power systems, including security region constraints, are typically nonlinear and non-convex. However, in certain cases, linearization techniques can be used to approximate the nonlinear constraints of power systems with a set of linear constraints. For instance, for small deviations from the nominal operating point, the nonlinear constraints can be approximated by linear constraints using a Taylor series expansion. Moreover, linearization techniques can be used to obtain a linear approximation of the constraints around a particular operating point. However, these linear approximations may not hold true for all operating points, and they may not capture the full range of nonlinear behaviors of the system. Therefore, while linearization techniques can be useful to analyze the behavior of power systems, they cannot fully capture the nonlinearities of the system.
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Could the central bank's historical record net loss for 2022, in the context of its monetary policy and speculative transactions in international financial markets, mean a decrease in security in the banking system?
The main purpose of a central bank's activities is to take care of the value of money, its stability against other currencies and the security of the banking system. However, since the 1970s, since the period of the rise of monetarism developed in accordance with Milton Fredman's concept of monetarism, the increase in the scale of economic globalisation, the transition of international monetary systems from the USD-based system, the system established after the Second World War in Bretton Woods to a system of free market exchange rates, the abandonment in the USA of gold parity with the USD currency, the growth of multinational corporations, the increased importance of speculative financial transactions carried out on foreign capital markets, including securities markets, etc. Central banks are also involved in the processes of stabilising the economy as part of anti-crisis programmes and protecting national labour markets, with the aim of limiting the scale of the increase in unemployment. In some countries, these new, additional central bank functions are added to the legal regulations shaping the functioning of the central bank. In some countries, the issue of linking the central bank's monetary policy is implemented informally.
For years, the central bank in Poland has also been conducting speculative transactions on international financial markets using various currencies and securities. For many previous years, the bank generated a net profit of PLN 9-10 billion of which 95 per cent of this profit was transferred to the state budget by the politically connected central bank to the government, instead of feeding the central bank's reserves and increasing the security of the financial system. For 2021, the central bank in Poland, i.e. the National Bank of Poland, generated as much as PLN 11 billion in net profit thanks to speculative transactions on the international financial markets, almost all of which went to the state budget rather than to central bank reserves, as usual. The annual profit generated by the central bank in Poland until 2021 was a consequence of, among other things, the monetary policy pursued by the bank, which consisted in successive depreciation of the domestic currency PLN against other currencies. However, for 2022, the National Bank of Poland unexpectedly raked in a historically record loss of PLN 17 billion. Could it be that the speculative transactions carried out in 2022 on the international financial markets turned out to be wrong this time? In addition, another key question arises: to what extent will this kind of situation result in a decrease in the level of security of the entire banking system?
In view of the above, I address the following question to the esteemed community of scientists and researchers:
Could the historically record net loss of the central bank for 2022, in the context of the monetary policy pursued and the speculative transactions carried out on the international financial markets, mean a decrease in security in the banking system?
And what is your opinion on this?
What is your opinion on this subject?
Please respond,
I invite you all to discuss,
Thank you very much,
Best wishes,
Dariusz Prokopowicz
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Yes, net loss of central bank lost the public confidence regarding banking system, which effect the country macroeconomics policy i. e. stability.
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I want to pick a published dataset (after giving proper citation and securing copyright also) from one article and after that I want to solve it with different software and compare it with the published results. Is it ethically fine or there is some violation of ethics?
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In general, it is allowed to use a dataset for further analysis or to solve a problem using alternative techniques/software if the dataset is publicly available and the published paper includes a reference to it. However, it is crucial to make sure that you cite the original paper as the dataset's source and give the authors of that paper the correct credit.
The legal ability to utilize the dataset for your intended purposes must also be confirmed. Some datasets might only be usable for non-commercial purposes, require permission from the original authors, or have other limitations on their use. To make sure you are using the dataset properly, you should carefully study any conditions of use or licensing agreements that are related to it.
The methods and tools you are employing should also be carefully evaluated to see if they are acceptable for the dataset and the research topic you are attempting to answer. It's possible that specific techniques or software won't work well with the dataset you're using or won't yield accurate findings. As a result, it's crucial to carry out the proper validation and verification of any results that were acquired using the dataset and the methods/software you've selected.
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Please suggest me Ph.D. topic on cybersecurity particularly considering either app security, context-aware systems, and small devices including but not limited to embedded control systems, IoT applications, and sensor networks. Or a topic relates to AI & Machine Learning.
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I would suggest that research needs to be done on techniques of corruption of Generative AI by the introduction of malware that presents biased data to change the results incorporated by the AI "learning algorithms" in a malicious way, and so are able to bias the "training data" incorporated into generation of extensions to the analysis routines. It is concerning to me that most of the recent work I have seen seems to be concentrating on the "short term" result, and not very much is looking for "longer term" (i.e. the focus of Malware detection using Machine learning is on immediate detection and seems to be lacking consideration of an attack based on gradual corruption introduced over longer and even potentially asynchronous time periods)
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Is the increasing scale of populist short-sighted economic state interventionism and the growing influence of the state in the economy generating emerging economic and/or financial and social crises that are increasingly serious, increasingly severe for society?
It has happened on more than one occasion that attempts to significantly increase the scale of "manual control" of the economy, economic state interventionism, expansion of public sectors, the system of central institutions, government-controlled public institutions and enterprises operating as state-owned companies, etc., have ended in the occurrence of another economic and/or financial crisis, larger than the previous ones. Economic crises, including raw material crises, were more than once initiated by the unexpected occurrence of certain external factors such as a sudden and rapid increase in the price of raw materials and/or also other production factors. This happened during the raw material crises of the 1970s. The government, in the situation of the development of a raw material crisis, in an attempt to limit the scale of this crisis and the scale of the also developing economic crisis, the increasing level of unemployment and the decrease in economic activity of companies and enterprises, changes its economic policy by introducing certain additional, interventionist, anti-crisis solutions and instruments of fiscal, monetary policy, etc.
The scale of the state's influence in the economy has been growing in Poland in recent years. An increase in the scale of the so-called anti-crisis economic state interventionism; an increase in the scale of the introduction by the government into the economy of additional money not bound by the parity of produced economic goods as an element of interventionist shaping of economic processes; an increase in the scale of the participation of the state treasury in the shareholding of companies and enterprises of some, including strategic sectors of the economy; an increase in the scale of monopolisation of markets by sectors in which corporations dominated by the state treasury operate; the creation by people working in the government of new institutions, agencies, foundations, institutes, etc., which pursue the combined interests of decision-makers, political parties and sometimes also informally linked to business. pursuing the combined interests of decision-makers with the objectives of political party functioning and sometimes also informally linked to business; the increasing scale of the use of central banking monetary policy instruments and fiscal policy instruments in government economic programmes pursuing specific objectives in the increased scale of state influence in economic processes; the increasing scale of the state's system of public finances in the context of the overall finances realised in the economy; the increasing scale of indebtedness of the state's system of public finances without an analogous scale of the increase in investments realised within the framework of the public and commercial sectors of the economy are only some of the key aspects of the increase in the scale of economic state interventionism that has taken place in recent years.
In view of the above, I address the following question to the esteemed community of scientists and researchers:
Is the increasing scale of populist short-sighted economic state interventionism and the growing influence of the state in the economy generating the emerging economic and/or financial and social crises that are becoming more and more severe for society?
And what is your opinion on this?
What is your opinion on this subject?
Please respond,
I invite you all to discuss,
Thank you very much,
Best wishes,
Dariusz Prokopowicz
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opined that different economic systems cannot be mixed, i.e. the planned capitalist economy, plus the promised welfare bonus, will not work. The mixing approach lead, for example, to the tragic katastroIka of the Soviet system; the Yugoslav case should also be remembered.
To my knowledge and experience, Biblical or Christian Social TeachIngs (ethics) can also be applied in the capitalist market economy, with respect to legal standards of social security (basic health insurance, retirement schemes, limited unemployment aid, and the like), but that depends on the organized bargaining power of the laboring class, which is generally expressed by strong popular parties.
In this sense, dear Dariusz Prokopowicz ,John Komlos offers good scientific work, with respect to creative future solutions:
______________
The Church's teaching on ownership diverges radically from collectivism as proclaimed by Marxism and "rigid" capitalism. The primacy of the person over things, joint ownership of the means of work.
Pope John Paul II
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How can the use of blockchain increase security and transparency in real estate transactions carried out by a real estate company and how can this technology be applied viably and efficiently?
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The use of blockchain technology can increase security and transparency in real estate transactions by providing a secure, immutable and decentralized digital ledger that records all transactions. Here are some ways that blockchain technology can be applied viably and efficiently in real estate transactions:
1. Smart Contracts: Blockchain-based smart contracts can be used to automate real estate transactions, eliminate intermediaries, and ensure that all parties fulfill their obligations. Smart contracts can also reduce transaction time frames and mitigate fraud and errors.
2. Property Ownership Tracking: Blockchain technology can be used to track property ownership, transfer and registration in a secure and transparent manner. The ability to track property ownership can reduce the risk of errors, fraud and minimize legal disputes.
3. Property Valuation: Blockchain technology can be used to monitor the local real estate market and provide real-time property valuation. This capability can help ensure that properties are bought and sold at fair market value.
4. Tokenization : Tokenization enables the division of real estate assets into fractions that can be represented by digital tokens. These tokens can be traded on blockchain-enabled platforms, providing more liquidity to real estate investments.
In conclusion, the use of blockchain technology can increase security and transparency in real estate transactions by providing a secure and transparent digital ledger, automating real estate transactions, reducing the risk of fraud, and mitigating disputes. Viability and efficiency can be achieved by leveraging smart contracts, asset tracking, property valuation, and tokenization.
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the question answers itself
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i'm laughing because i'm gonna guess Wali said the Internet would never amount to much and that cell phones weren't his idea, so they aren't any good either... :)~
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Greetings everyone!
I am conducting a research on security. So that I am doing a survey on different existing public datasets on security. In recent years some papers are published using CCC (Cyber Clean Center) dataset. But I can't find any public link to download the dataset.
Is there anyone who can help me to find the CCC (Cyber Clean Center) dataset in any extension?
I will be thankful.
Thanks.
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Unfortunately, the Cyber Clean Center does not make its dataset publicly available. You may be able to find some information about the dataset by visiting the CCC website and reading any information they have published about their data.
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#specialissue #CallforPapers CMC-Computers, Materials & Continua new special issue “Innovative Security for the Next Generation Mobile Communication and Internet Systems”is open for submission now.Submit your research now and contribute to advancing mobile communication security!👉 At link: https://www.techscience.com/cmc/special_detail/MCIS
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Innovative Security for the Next Generation Mobile Communication and Internet System
1. Encryption of data: Data encryption is the process of transforming data into a form that is difficult or impossible to decipher, making it unreadable to anyone except those who possess the correct encryption key. This can be accomplished through the use of strong encryption algorithms such as AES, RSA, and 3DES.
2. Multi-factor authentication: Multi-factor authentication (MFA) is an authentication process that requires two or more factors such as a username, password, and fingerprint scan or facial recognition to verify identity. By using MFA, organizations can significantly reduce the risk of unauthorized access and protect sensitive data.
3. Mobile device management: Mobile device management (MDM) is a set of tools and processes used to secure and manage mobile devices. MDM can provide remote device management, including the ability to remotely lock, wipe, or locate a device.
4. Secure cloud storage: Cloud storage solutions such as Google Drive, Dropbox, and iCloud offer secure storage of data, ensuring that only authorized users can access it. These solutions encrypt data both in transit and at rest, helping protect it from unauthorized access.
5. Virtual private networks: Virtual private networks (VPNs) are used to securely connect two or more devices over the internet, allowing them to communicate with each other securely. A VPN encrypts all data in transit, helping protect it from interception.
6. Two-factor authentication: Two-factor authentication (2FA) is an authentication process that requires users to provide two pieces of evidence in order to gain access, such as a username, password, and one-time code generated by a mobile app or device. This helps protect against unauthorized access and malicious actors.
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Micro Focus provides software for code testing, code security, application delivery, content management and Visual Cobol free of charge to enable teachers and researchers to use this software within their work. For students of course this is very valuable as it gives exposure to real world applications without any associated cost to the institution.
Further details on this particular program can be found at: https://www.microfocus.com/en-us/academic-software-program
Does anyone know of any other companies that make similar offers to academics and if so for what software.
Thanks for your input.
Kind regards
Peter
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1. Microsoft: Microsoft offers free software for teaching and research purposes under its Microsoft Azure for Research program.
2. Apple: Apple provides free software for teaching and research through their Apple Academic Program.
3. Adobe: Adobe provides free software for teaching and research purposes through their Education Exchange.
4. Autodesk: Autodesk provides free software for teaching and research purposes through their Autodesk Education Community.
5. Google: Google provides free software for teaching and research through their Google for Education program.
6. IBM: IBM provides free software for teaching and research purposes through their Academic Initiative.
7. MathWorks: MathWorks provides free software for teaching and research purposes through their University Program.
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The Security Council has primary responsibility, under the United Nations Charter, for the maintenance of international peace and security. Today the P5 (permanent members) or simply speaking just 5 countries determine the fate of millions during a seize, war or invasion. -by their "veto power by nullifying any attempt to join a conflict or break down an invasion. These countries being the United States, China, France, Russia, and the United Kingdom. However this group has now become polarized due to which most actions are vetoed out by either group A or B.
Group A: China, Russian Fed
Group B: USA, UK, France
Other countries who have nuclear capability but do not have a permanent seat being Pakistan, India, Israel, and North Korea. So should some of these countries also be included in the P5 to make it P7 and bring more stability and rationality to the powers given to P5, who in most cases cannot really work together and oppose each other using their Veto card.
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When the United Nations was established and the permanent members of the Security Council were determined, this was related to a specific international context that resulted from the end of the Cold War, but now, after nearly eight decades have passed since that time, the composition of the Security Council must be reconsidered, and permanent membership in it granted to other countries from different continents. In a manner consistent with the nature of international developments and the balance of power that took place during those past decades, Currently, new powers have risen and the map of international powers has changed. It is inconceivable for the continent of Africa to remain without any representation in the Council. The same is the case with regard to Latin America. As for the continent of Asia, it has become the home of the most important emerging powers now. Therefore, its representation in the Council must be expanded to include other countries such as India and Japan, and changing the composition of the Security Council will achieve a greater balance for international relations and how to deal with international issues that it studies
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Gig workers is type of worker community who work on contract basis and Employer is not guaranteed on job security.
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Imagine you are a gig worker named John, who works as a freelance graphic designer. John has been freelancing for the past few years and enjoys the flexibility that comes with being his own boss. However, he faces several challenges in his work.
Firstly, John doesn't have access to traditional benefits such as health insurance and retirement benefits. This is a significant challenge for him, as he has to bear all his medical expenses and doesn't have any retirement savings.
Secondly, John's income is not consistent. Some months he has several projects, while other months he struggles to find work. This makes it challenging for him to plan his finances, and he often finds himself dipping into his savings to cover his expenses during lean months.
Thirdly, John feels insecure about his job as a gig worker. Since he doesn't have a formal contract with his clients, he is always worried about losing work opportunities without warning.
Fourthly, John finds it challenging to find consistent work opportunities in his field. He spends a considerable amount of time and effort networking and reaching out to potential clients to secure work.
Fifthly, John works independently, and as a result, he often feels isolated and lonely. He misses the social interaction and support that comes with working in an office environment.
Finally, John faces legal and regulatory issues in his work. As a freelancer, he has to navigate complex tax laws and regulations, and he worries about whether he is complying with all the legal requirements.
In summary, John's story highlights the various challenges faced by gig workers. While gig work offers flexibility and independence, it also comes with its fair share of difficulties. It is essential for policymakers, employers, and other stakeholders to recognize these challenges and work towards creating a more supportive and equitable work environment for gig workers.
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How can artificial intelligence help improve cyber security systems and techniques in online and mobile banking?
In recent years, technologies that play an important role in the field of Industry 4.0, technologies that determine the current fourth technological revolution, including machine learning technologies, deep learning and artificial intelligence are finding their way into improving cyber security systems. Financial institutions, including commercial banks, are implementing a certain generation of artificial intelligence technologies into specific areas of banking in order to increase process efficiency, economic efficiency, etc. Artificial intelligence is already being used by banks to improve remote communication processes with customers, in call centre departments as part of the creation of automated remote communication systems and digitised adviser avatars, in the process of managing credit risk and other risk categories, and also in the area of cyber-security.Therefore, opportunities are emerging for the application of artificial intelligence technologies in improving cyber-security techniques and systems in various areas of cyber-security in online and mobile banking, including issues such as:
1. improving cyber-security techniques to protect the information systems of financial institutions, including banks, from external cyber-attacks via email and ransomware viruses.
2. improving cybercrime risk management systems for integrated internal information systems connected to the Internet.
3. Improving cyber security techniques implemented through the implementation of new Industry 4.0 technologies, including artificial intelligence, machine learning, Blockchain, multi-criteria simulation models, etc., and advanced analytical techniques such as Big Data Analytics, Business Intelligence.
4. improving the anti-spam systems used to protect email inboxes in order to increase the filtering out of emails where cybercriminals use phishing techniques and/or send malware and ransomware viruses in the background of the email.
5. Improving cyber-security techniques for online and mobile banking systems with a particular focus on mobile banking implemented on the bank's customer side using smartphones equipped with specific operating systems and web applications.
6. Analysis of the level of effectiveness and cyber security for biometric techniques for encoding access to information systems as an important factor in cyber security.
7. perfecting cyber-security techniques in integrated, internal, intranet information systems operating in financial institutions, including commercial banks characterised by a complex organisational structure and companies forming interconnected business entities.
In view of the above, financial institutions, including commercial banks, are implementing a certain generation of artificial intelligence technologies in various areas of banking, including in the improvement of cyber-security techniques and systems.
In view of the above, I address the following question to the esteemed community of scientists and researchers:
How can artificial intelligence help improve cyber-security systems and techniques in online and mobile banking?
What do you think about this topic?
What is your opinion on this subject?
Please respond,
I invite you all to discuss,
Thank you very much,
Best regards,
Dariusz Prokopowicz
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AI uses machine learning and deep learning to recognize patterns on the network and cluster them, it will then detect deviations or security incidents from the norm before responding to them. These patterns can help to improve security in the future. Similar potential threats can be detected and blocked early enough.
Regards,
Shafagat
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I'm pursuing Ms in Computer science. I'm search for research topic.
I've come across following areas. Can someone review and let me know if these can be research candidates?
1. Comparison of different full stack frameworks
2. Progressive web applications
3. Security in Full stack applications
Also, can someone help me narrow down to a topic in these?
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It's great to see that you are considering various research topics related to full stack development. The areas you've mentioned are indeed relevant and hold potential for research. Let me provide a brief overview and some suggestions to help you narrow down the topics:
* Comparison of different full stack frameworks: Studying the features, performance, and trade-offs of various full stack frameworks can be insightful. Instead of a generic comparison, you could focus on specific aspects or challenges, such as the ease of scalability, adaptability to emerging technologies, or how well these frameworks support serverless architectures.
* Progressive web applications (PWAs): PWAs are an exciting area of research as they bring the best of both web and mobile applications. You could study the factors that influence the adoption of PWAs, explore novel approaches to optimize performance and user experience, or investigate the challenges faced in integrating PWAs with emerging technologies like augmented reality or the Internet of Things.
* Security in Full stack applications: Security is always a critical concern in any development process. Research in this area could focus on identifying and addressing common security vulnerabilities in full stack applications, developing new techniques to ensure data privacy and protection, or examining best practices for secure authentication and authorization.
To narrow down your topic, consider reflecting on your personal interests, the relevance of the topic to the industry, and the potential impact of your research. Choose a topic that you find engaging and that can contribute to the field of full stack development.
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Despite making significant investments in security technologies, organizations continue to struggle with security breaches: Their adversaries are quick to evolve tactics and stay ahead of the technology curve. Humans may soon be overwhelmed by the sheer volume, sophistication, and difficulty of detecting cyberattacks. People are already challenged to efficiently analyze the data flowing into the security operations center (SOC) from across the security tech stack. This doesn’t include the information feeds from network devices, application data, and other inputs across the broader technology stack that are often targets of advanced attackers looking for new vectors or using new malware. And as the enterprise increasingly expands beyond its firewalls, security analysts are charged with protecting a constantly growing attack surface.
source: The future of cybersecurity and AI | Deloitte Insights
Applied Sciences | Special Issue: Smart Cyberspace and IoT Systems: Challenges and Future Trends (mdpi.com)
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Convergence around safety and security is having a significant impact on the cybersecurity challenges in IoT cyber critical infrastructures. It involves bringing together stakeholders from different disciplines, such as engineering, IT, and cybersecurity, to work together to ensure that IoT systems are secure and safe. Please see my paper titled "The Impact of Uncertified Practitioners on the Safety and Security of Critical Infrastructure Projects and Operations in the Operational Technology Domain" See also my Ph.D. thesis on "Safety and Information Security Fusion in Operational Technology, Towards a New Convergent Holistic Risk Management Model" and my paper on "The role of Artificial Intelligence in predicting and preventing cyber-attacks in critical infrastructure" for further inputs.
Further, AI in cybersecurity is an exciting development that has the potential to significantly improve the security of IoT systems, particularly in critical infrastructure settings.
The following are some ways in which convergence around safety and security is impacting cybersecurity challenges in IoT cyber critical infrastructures:
  1. Improved collaboration
  2. Common standards and best practices
  3. Risk assessment and management
  4. Continuous monitoring and improvement
My response give to the Question: "How would a coordinated global cyber attack impact critical infrastructure and what measures can be taken to prevent and mitigate such an event?" | here on ResearchGate may also be helpful.
The IoT (Internet of Things) has revolutionized the way we live, work, and interact with technology. However, it has also brought about significant cybersecurity challenges, particularly in cyber critical infrastructures such as power grids, transportation systems, and healthcare facilities.
Some of the key cybersecurity challenges in IoT cyber critical infrastructures include:
  1. Scale and complexity
  2. Diverse architectures
  3. Lack of standards
  4. Resource constraints
  5. Legacy systems
To address these challenges, there is a growing need for convergence around safety and security as the key response. This means that security must be integrated into the design, development, and deployment of IoT systems from the outset, rather than being an afterthought.
In recent years, AI-driven cybersecurity implementations have become increasingly popular, particularly in the area of threat detection and response. One example of AI-driven cybersecurity implementation is the application of AI to PLCs (Programmable Logic Controllers). PLCs are commonly used in industrial control systems (ICS), which are used to control and monitor critical infrastructure systems such as power plants and water treatment facilities.
*Applying AI to PLC capabilities in OT environments*
By applying AI to PLCs, it is possible to detect anomalies and potential cyber threats in real-time. For example, AI can be used to detect unusual patterns in the data being processed by the PLC, which may indicate a cyber attack. AI can also be used to identify vulnerabilities in the PLC's code and configuration, which can then be addressed to improve the system's security.
The sheer scale and complexity of IoT systems make it challenging to secure them effectively. IoT devices and systems have diverse architectures, making it difficult to implement a unified security approach. There is a lack of common standards for IoT devices and systems, which can make it difficult to ensure consistent security across different systems with many IoT devices having limited resources, such as processing power, memory, and battery life, which can make it challenging to implement strong security measures. finally many critical infrastructure systems are based on legacy technology that may not have been designed with security in mind.
I specialize on the topic of convergence in IT/OT therefore I see convergence around safety and security as a key challenge. Convergence includes facilitating better collaboration between different stakeholders, allowing them to work together to identify and address cybersecurity challenges. This collaboration ensures that security is integrated into the design, development, and deployment of IoT systems from the outset.
Convergence around safety and security promotes the use of common standards and best practices for IoT security. This approach ensures that all systems are secured in a consistent and effective manner, reducing the risk of vulnerabilities or weaknesses in IoT systems.
Convergence around safety and security is enabling stakeholders to perform risk assessments and management, helping to identify potential threats and vulnerabilities in IoT systems. This approach ensures that security measures are tailored to the specific risks associated with each IoT and finally convergence around safety and security promotes the use of continuous monitoring and improvement for IoT security. This approach ensures that security measures are updated and improved regularly, to keep up with evolving threats and vulnerabilities.
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I need the protocols for tagging tropical mangrove seedings. They need to be numbered and last for at least 10 years (3-4 year censuses).  The only tapes I've been able to find are Dymo tapes and I can control the length and punch a hole for securing it to the seedling.  We were looking for something to secure it to the mangrove seedling like zip ties or something similar.  We also need to purchase over 1000 of them, so price is a key issue.  Any suggestion would be greatly appreciated. If you have experience with long term mangrove seedlings surveys, other suggestions would be welcomed too.
Thanks to all,
Alia.
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Andrew's correct to the extent that no label and fixing can be completely relied upon over 10 years, especially in saline conditions and having to withstand wave energy from time to time. Conventionally the label itself could be of metal or engraved plastic, but metals will corrode in seawater and for the latter you'd need an engraving machine. The cheapest would be aluminium 'tree tags', which are small discs (about 3cm across) stamped with a number and that can be bought in the thousands. Perhaps you could paint them with a marine paint to make them more durable. In tree surveys tree tags are generally nailed to the trunk, the nail only partly driven in to allow for radial growth, but I imagine that better options in your case would be to have a loose attachment of wire or cord, or to fix the tag to a stake driven into the substrate adjacent to the tree. Perhaps an engraved wooden label would be best, or an adjacent stake could be engraved (you could then use local materials). A stake would also be easier to find than a label. Finally, if all else fails, you could engrave the tree itself!
Philip
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What is the value of biological diversity in food and ecological security and does increased biodiversity increase food production?
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Biodiversity for food and agriculture is vital for food security. The erosion of biodiversity will undermine the capacity of agricultural systems to adapt to changing conditions and shocks, such as climate change, and outbreaks of pests and diseases that may jeopardise food security and livelihoods. Biodiversity plays a crucial role in human nutrition through its influence on world food production, as it ensures the sustainable productivity of soils and provides the genetic resources for all crops, livestock, and marine species harvested for food. Biodiversity is a key resource in efforts to increase food production while limiting negative impacts on the environment. Biodiversity in ecosystems, species, and individuals leads to greater stability. For example, species with high genetic diversity and many populations that are adapted to a wide variety of conditions are more likely to be able to weather disturbances, disease, and climate change. Biodiversity is also a component of natural capital, and it is vital to any farming system. Biodiversity refers to the variety and variability of life, at a range of levels including species and ecosystems. Without this variety, ecological systems such as water filtration and nutrient cycling could not function. Biodiversity increases productivity and biodiversity increases stability of ecosystems. Biodiversity is therefore strongly linked to the resilience of systems and is essential for food security. High biodiversity can maximize production levels, which are sustained through beneficial impact of ecosystem services for agricultural, modified and natural ecosystems. The biggest impact of biodiversity is on the environment. Healthy ecosystems help to maintain the Earth's natural processes. Soil turnover, water purification, pest control, and other processes wouldn't be possible without the species that support them. Biodiversity provides vital ecosystem functions such as soil fertilization, nutrient recycling, pest and disease regulation, and erosion control and crop and tree pollination. Biodiversity, including functions of ecosystems, offers a large variety of goods and services that support human life: provision of food; fuel and construction materials; purification of air and water; stabilization and moderation of global climate; moderation of floods, droughts, extreme temperatures
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Thanks to those who respond in detail to my need for several opinions
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They are intertwined and very critical to further biopsychosocial development.
Rich
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Does lending denominated in a foreign currency, taking into account currency risk, generate a significantly higher overall level of credit risk compared to lending in domestic currency?
For example, lending denominated in foreign currency generates additional currency risk so it may increase the overall level of credit risk compared to lending in domestic currency. In addition, sometimes commercial banks also use abusive clauses in their loan agreements when granting business, investment or mortgage loans in foreign currency, which are the result of unethical business practices by the bank and can result in a strong asymmetry of information between the bank and the borrower, the bank taking advantage of a much weaker negotiating position of its clients and hidden, additional costs being charged to the borrower. Such practices were used by a significant part of commercial banks in Poland in the period of several years just before the onset of the global financial crisis of 2007-2099. At that time some commercial and investment banks predicted the occurrence of this crisis on the basis of an analysis of their lending activity, the determinants of the macroeconomic environment and the situation and changes in trends on capital markets. The banks operating in a developing country such as Poland, a country characterised by its own characteristics, knew that by applying unreliable, unethical business practices towards borrowers, by having incompletely secured credit positions, the highly and historically overvalued market valuations of real estate and securities would soon start to fall, that the trend of several years of a bull market in capital markets would change to a stock market crash, which would result in a significant change in trends on currency markets as well. In contrast, borrowers taking out such mortgages denominated in foreign currencies, especially CHF, did not have this kind of knowledge. This is due to the fact that most borrowers do not deal on a daily basis with the analysis of banks' lending activities, the procedures for examining the borrower's creditworthiness and the bank's credit risk, the problems of credit risk management, both on an individual basis with regard to a single credit transaction and on a portfolio basis, i.e. in terms of managing the credit risk of entire portfolios of loans granted by the bank. Banks, on the other hand, are familiar with this issue because they deal with it on a daily basis and are obliged to do so by banking supervisory institutions. However, apparently these banking supervisory institutions as well as consumer and competition protection authorities, bank arbitrage institutions, central banks, etc. are not able to fully verify on an ongoing basis, as part of their ongoing monitoring, the issue of the integrity of commercial and investment banks' application of banking practices in lending, including the application of business ethics, the non-application of abusive clauses in loan agreements, the application of too much asymmetry of information to customers, the use of their advantage at the negotiating level. In order for these mortgages denominated in a foreign currency, in CHF, to sell well, so banks constructed models for calculating the creditworthiness of a potential, individual borrower in such a way that mortgages granted in a foreign currency turned out to be cheaper for borrowers than analogous loans granted in the domestic currency, i.e. in Poland in PLN. The results of the calculated creditworthiness presented to potential borrowers were such that the calculated creditworthiness for a loan granted in CHF was set at a significantly higher maximum loan amount that could be granted compared to an analogous loan granted in the domestic currency of PLN.
In view of the above, I would like to address the following question to the esteemed community of scientists and researchers:
Does the granting of loans denominated in a foreign currency, taking into account currency risk, generate a significantly higher overall level of credit risk compared to loans granted in domestic currency?
What do you think about it?
What is your opinion on this subject?
Please respond,
I invite you all to discuss,
Thank you very much,
Best regards,
Dariusz Prokopowicz
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Imo, the credit risk depends mainly on the overall strength of a national economy; if the national economy of a country is significantly weaker, the lending practice in foreign currency leads to greater credit risk than in domestic currency.
It is never good to put a strong and weak horse in a harness.
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The links, dear Dariusz Prokopowicz , are documenting one recent lesson of transition economics as per contemporary experience.
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You can try to reach the author to see if it was a mistake and correct it. If that fails, take a look at:
and follow the instructions provided in the link.
Regards
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