Science topic

Computer Networks - Science topic

Deals with the various aspects and domain of Computer Networks and Communication, Cloud, and Grid Computing
Questions related to Computer Networks
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In the realm of cybersecurity, Transport Layer Security (TLS) is widely used to secure communications over a computer network. Despite its robust encryption mechanisms, TLS is still susceptible to Man-in-the-Middle (MitM) attacks under certain conditions. A MitM attack involves an attacker secretly intercepting and possibly altering the communication between two parties who believe they are directly communicating with each other.
  • What are the indicators of a potential MitM attack in a TLS-secured environment?
  • Discuss any tools or methodologies used to detect MitM attacks.
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A Man-in-the-Middle (MitM) attack in the context of Transport Layer Security (TLS) exploits the communication between two parties, such as a client (eg, a browser) and a server (eg, a website), to intercept, decrypt, or data in transit. TLS is designed to secure such communications, but attackers may exploit vulnerabilities in implementation, configuration, manipulation, or trust mechanisms to bypass it.
Steps in a MitM Attack on TLS :
  1. Interception: The attacker places themselves between the client and the server. This can be done through: DNS Spoofing: Redirecting the client to a malicious server. ARP Spoofing: Altering the local network to route traffic through the attacker's system. Wi-Fi Eavesdropping: Setting up a rogue Wi-Fi hotspot to capture traffic.
  2. TLS Spoofing/Impersonation: The attacker intercepts the client's request to establish a secure TLS connection with the server. Instead of directly connecting to the server, the attacker impersonates the server to the client by presenting a fake or self-signed certificate.
  3. Certificate Manipulation: If the client does not properly verify the server's certificate, the attacker can present a fraudulent certificate. This might occur in cases where the client ignores certificate warnings or the attacker exploits a Certificate Authority (CA) to issue a malicious certificate.
  4. Data Decryption : Once the connection is established, the attacker decrypts and accesses the communication. The attacker can: Record sensitive information like usernames, passwords, or credit card numbers. Modify or inject data into the communication stream.
  5. Re-encryption: To avoid detection, the attacker re-encrypts the data and forwards it to the server as if it came from a legitimate client.
Mechanisms to Mitigate MitM Attacks on TLS :
  1. Certificate Validation: Ensure the client verifies the server certificate against trusted Certificate Authorities (CAs). Use Extended Validation (EV) certificates for additional trustworthiness.
  2. Public Key Pinning (HPKP): Pin the server's public key or certificate in the client. This prevents accepting rogue certificates even if issued by a compromised CA. However, HPKP is now deprecated in favor of Certificate Transparency (CT).
  3. Certificate Transparency (CT): Maintain a public ledger of issued certificates to detect rogue or fraudulent certificates.
  4. Secure CA Practices: Use robust security measures for Certificate Authorities to prevent misuse or compromise. Deploy mechanisms like OCSP stapling to validate the certificate revocation status in real time.
  5. TLS Version and Cipher Suites: Use the latest versions of TLS (eg, TLS 1.3) which mitigate vulnerabilities in older versions (like SSL or early TLS versions). Use strong cipher suites that provide Perfect Forward Secrecy (PFS) to ensure compromised keys cannot decrypt past communications.
  6. HSTS (HTTP Strict Transport Security): Implement HSTS headers to enforce the use of HTTPS, ensuring all communications are over a secure channel.
  7. Client and Server Authentication: Implement mutual TLS authentication where both client and server verify each other's certificates.
  8. DNS Security: Use DNSSEC (Domain Name System Security Extensions) to prevent DNS spoofing and ensure DNS records are signed and validated.
  9. User Education: Educate users to avoid connecting to suspicious Wi-Fi networks and to heed browser warnings about invalid certificates.
  10. Network Monitoring: Use Intrusion Detection/Prevention Systems (IDS/IPS) to detect unusual traffic patterns or certificate anomalies indicative of a MitM attack.
  11. In Conclusion, TLS is designed to provide secure communication, but a Man-in-the-Middle attack can exploit vulnerabilities in implementation or trust. By employing strong certificate validation, using updated TLS protocols, and securing the DNS infrastructure, organizations and users can effectively mitigate MitM risks in TLS communications.
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I understand that it is possible to analyze this issue mathematically to estimate the memory requirements for TLS. However, I am particularly interested in understanding how much memory is actually utilized in current implementations. Insights on this matter would be greatly appreciated. Ideally, if anyone could reference relevant papers or studies, that would be perfect.
Moreover, my interest extends beyond memory usage; I am equally curious about the time required to perform a TLS handshake in practice.
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The TLS (Transport Layer Security) handshake is a critical process for establishing secure communications over the internet. Here are some pros and cons of the TLS handshake in practice:
Pros:
  1. Security: The primary advantage of the TLS handshake is its ability to establish a secure connection between a client and a server. It ensures that data transmitted over the connection is encrypted and protected from eavesdropping and tampering2.
  2. Authentication: The TLS handshake involves the exchange of digital certificates, which helps verify the identities of the communicating parties. This prevents man-in-the-middle attacks and ensures that users are connecting to legitimate servers.
  3. Data Integrity: TLS provides mechanisms to ensure that data is not altered during transmission. This is achieved through the use of cryptographic hash functions and message authentication codes (MACs).
  4. Widely Adopted: TLS is a widely adopted standard for securing internet communications. It is used in various applications, including web browsing, email, instant messaging, and VoIP.
Cons:
  1. Performance Overhead: The TLS handshake involves multiple steps, including key exchange and certificate verification, which can introduce latency and increase the time it takes to establish a connection3.
  2. Complexity: Implementing and managing TLS can be complex, requiring proper configuration and maintenance of digital certificates. Misconfigurations can lead to security vulnerabilities.
  3. Resource Intensive: The cryptographic operations involved in the TLS handshake can be resource-intensive, particularly for devices with limited processing power. This can impact the performance of servers and clients.
  4. Certificate Management: Managing digital certificates, including obtaining, renewing, and revoking them, can be cumbersome and costly. Failure to properly manage certificates can result in expired or compromised certificates.
Overall, while the TLS handshake provides robust security and authentication, it comes with trade-offs in terms of performance and complexity. Proper implementation and management are essential to maximize its benefits and minimize its drawbacks.
If you have any other questions or need further details, feel free to ask!
What is Transport Layer Security (TLS)? Strengths and Vulnerabilities Explained
https:/www.g2.com/articles/ssl-tls-handshake
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2025 4th International Conference on Computer, Artificial Intelligence and Control Engineering (CAICE 2025) is to be held in Hefei, China in January 10-12, 2025.
Conference Website: https://ais.cn/u/YNfu22
---Call for papers---
The topics of interest for submission include, but are not limited to:
(I) Computer
· Edge Computing and Distributed Cloud
· Architecture, Storage and Virtualization
· Cloud Computing Technologies
· Deep Learning and Big Data
· Computer networks
......
(II) Artificial Intelligence
· Artificial Intelligence Applications
· Pattern Recognition and Machine Learning
· AI Languages and Programming Techniques
· Cybersecurity and AI
· Artificial Intelligence and Evolutionary Algorithms
......
(III) Control Engineering
· Automatic Control Principles and Technology
· Design, modeling and control of precision motion systems
· Vibration analysis and control
· Fuzzy control and its applications
· Fractional order system and control
· Flexible robotics, soft robotics
· Smart automation
---Publication---
All papers will be reviewed by two or three expert reviewers from the conference committees. After a careful reviewing process, all accepted papers will be published in ACM conference proceeding, and submitted to EI Compendex, Scopus for indexing.
---Important Dates---
Full Paper Submission Date: December 19, 2024
Notification Date: December 25, 2024
Registration Date: December 29, 2024
Conference Dates: January 10-12, 2025
--- Paper Submission---
Please send the full paper(word+pdf) to Submission System:
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Is this conference hybrid or physical only?
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Hello everyone,
I am currently investigating the application of Poisson distribution in detecting attacks in wireless sensor networks. Does anyone have any knowledge of studies in this field? I am looking for articles or resources that specifically address this topic. Any help or guidance in this area would be greatly appreciated.
Thank you,
Mehdi Najafi
Master's Student in Computer Networks, Islamic Azad University of Hamedan
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The Poisson distribution is quite useful in detecting attacks in wireless sensor networks (WSNs) due to its ability to model the occurrence of rare events over a fixed period or space. Here are a few ways it can be applied:
Event Detection: In WSNs, the Poisson distribution can model the arrival of packets or events. If the rate of packet arrival deviates significantly from the expected Poisson distribution, it may indicate an attack, such as a Denial of Service (DoS) attack.
Node Deployment: The spatial distribution of sensor nodes can be modeled using a Poisson point process. This helps in evaluating the coverage and connectivity of the network, which is crucial for detecting and mitigating attacks.
Intrusion Detection: By analyzing the frequency and pattern of network traffic, the Poisson distribution can help identify anomalies that suggest malicious activities. For example, a sudden spike in traffic could indicate a jamming attack.
Trust Models: Poisson distribution-based trust models can be used to assess the reliability of nodes in the network. Nodes that deviate from the expected behavior can be flagged as potentially compromised.
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Hello everyone,
I am currently conducting research on Tiny ML in WSN. Specifically, I am seeking information and articles related to in the field of Wireless Sensor Networks and Tiny ML.
Could anyone suggest relevant resources or articles? Any help or guidance would be greatly appreciated.
Thank you,
Mehdi Najafi
Master's Computer Networks Student at Islamic Azad University of Hamedan
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Artificial Intelligence (AI) and Machine Learning (ML) have experienced rapid growth in both industry and academia. However, the current ML and AI models demand significant computing and processing power to achieve desired accuracy and results, often restricting their use to high-capability devices. With advancements in embedded system technology and the substantial development in the Internet of Things (IoT) industry, there is a growing desire to integrate ML techniques into resource-constrained embedded systems for ubiquitous intelligence. This aspiration has led to the emergence of TinyML, a specialized approach that enables the deployment of ML models on resource-constrained, power-efficient, and low-cost devices. Despite its potential, the implementation of ML on such devices presents challenges, including optimization, processing capacity, reliability, and maintenance. This article delves into the TinyML model, exploring its background, the tools that support it, and its applications in advanced technologies. By understanding these aspects, we can better appreciate how TinyML is transforming the landscape of AI and ML in embedded and IoT systems.
Regards,
Shafagat
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2024 4th International Conference on Electronic Information Engineering and Computer Science (EIECS 2024) will be held on September 27-29, 2024 in Yanji, China.
Conference Website: https://ais.cn/u/7n6Vva
---Call for papers---
The topics of interest for submission include, but are not limited to:
◕ Electronic Information Engineering
· Signal processing
· Wireless network
· Information system
· Next generation mobile communication technology
· Internet of things
......
◕ Computer Science
· Computer system
· Artificial intelligence
· Machine learning and deep learning
· Pattern recognition
· Computer vision and graphics
......
---Publication---
All accepted full papers will be published in the conference proceedings and will be submitted to EI Compendex / Scopus for indexing.
---Important Dates---
Registration Deadline: August 30, 2024
Final Paper Submission Date: August 30, 2024
Conference Dates: September 27-29, 2024
--- Paper Submission---
Please send the full paper(word+pdf) to Submission System:
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I am interrested
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会议征稿:第四届智能通信与计算国际学术会议(ICICC 2024)
Call for papers: 2024 4th International Conference on Intelligent Communications and Computing(ICICC 2024) will be held in Zhengzhou, China during October 18-20, 2024.
重要信息
大会官网(投稿网址):https://ais.cn/u/2QJFR3
大会时间:2024年10月18-20日
会议地点:中国·郑州
收录类型: EI, SCOPUS
主办单位:郑州大学、河南省通信学会
会议详情
第四届智能通信与计算国际学术会议(ICICC 2024)将于2024年10月18-20日在中国郑州隆重举行。会议旨在为从事智能通信与计算研究的专家学者、工程技术人员、技术研发人员提供一个共享科研成果和前沿技术,了解学术发展趋势,拓宽研究思路,加强学术研究和探讨,促进学术成果产业化合作的平台。大会诚邀国内外高校、科研机构专家、学者,企业界人士及其他相关人员参会交流。
会议征稿主题(包括但不限于)
1. 智能通信方向
智能计算应用
信息系统安全与管理
计算机网络与通信
移动通信和无线技术
通信网络及其管理
网络工程与安全
信息安全算法与协议
5g移动通信和智能计算通信
智能通信/信息安全
2. 计算方向
进化算法
启发式算法
粒子群优化
混合智能算法
人工智能
人工神经网络
机器学习
生物计算
DNA计算
出版信息
会议的所有投稿需经过3轮专家审稿,最终录用的论文将以会议论文集出版,收录进IEEE Xplore数据库,见刊后由期刊社提交至 EI Compendex和Scopus检索。
投稿参会链接:https://ais.cn/u/2QJFR3
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You may find huge raw data for it at www.rawdatalibrary.net
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Please provide references if possible.
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Issues at the Data Link layer (Layer 2 of the OSI model) can indeed lead to the termination of a network connection. Here are a few key problems that could cause this:
Collision and Collision Domains: In networks like Ethernet, data packets can collide when multiple devices try to send data simultaneously. If collisions are too frequent, it might lead to connection termination.
MAC Address Issues: Every device on a network has a unique MAC (Media Access Control) address. Problems like duplicate MAC addresses can disrupt communication.
Frame Loss or Corruption: If frames (the data unit at Layer 2) are lost or become corrupted (due to interference, poor cabling, etc.), it can result in connection drops.
Switching Loops: These occur when there are multiple paths between switches but no mechanism like Spanning Tree Protocol (STP) to prevent loops. It can lead to network floods and eventually connection termination.
Buffer Overflow: If network devices' buffers are overloaded and can't process all incoming frames, it can result in dropped frames and connection issues.
For more in-depth information and references, you might want to check out resources like "Computer Networking: A Top-Down Approach" by Kurose and Ross or Cisco's networking documentation. They provide comprehensive insights into network layer issues and their impacts.
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can someone help me on this?
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Sure, let's talk about networking right at your desktop! It's actually quite interesting.
Runts, Late Collisions, CRC Errors: These are common network issues. Runts are packets that are smaller than the minimum allowed size. Late collisions happen when devices try to send data at the same time but collide. CRC (Cyclic Redundancy Check) errors occur when data gets corrupted during transmission.
Desktop NICs (Network Interface Cards): Most desktop NICs can detect these errors. They're pretty smart! They often have built-in mechanisms to identify such issues and usually provide some form of error reporting.
Building a Program: Creating a program to monitor these errors is definitely possible. You’d typically use network monitoring tools or software that can interface with your NIC. The program would access the NIC's statistics and error counters to report these issues.
How to Do It: You'd need to dive into network programming. Using APIs or libraries that allow access to low-level network device information is key. Languages like C or Python, along with libraries suitable for network programming, would be your tools of choice.
In short, yes, you can totally create a program to monitor runts, late collisions, CRC errors, and the like, right from your desktop. It’s a neat way to keep an eye on your network health!
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It's great if you can explain how to identify those issues as well.
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Manula Manjitha Restarting a router, also known as the good old "turn it off and on again" method, is a surprisingly effective fix for several common network issues. Here's when you might want to give it a try:
Slow Internet Speeds: If your internet feels like it's moving at a snail's pace, a quick router restart can often kick things back into high gear.
Intermittent Connectivity: If you're losing connection every now and then, a restart can help reset the connection and might solve the issue.
Device Connectivity Problems: Sometimes specific devices struggle to connect to the network. Restarting the router can help clear any minor glitches causing this.
After a Network Change: Made any changes to your network settings? A restart helps ensure all changes are correctly applied.
Overheating: Routers can get tired too, especially if they're on 24/7. Restarting can give it a little breather and cool things down.
To identify these issues, keep an eye on your internet speed, check if your device keeps losing the Wi-Fi signal, or if a particular device can't connect. Also, if your router feels hot to the touch, it might need a quick break.
Remember, restarting your router is like giving it a mini-vacation; it often comes back refreshed and ready to go!
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Provide references if possible.
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IP header damage, or corruption, can happen due to various reasons, not just limited to physical layer issues. Let's break it down:
Physical Layer Issues: Sure, things like signal degradation, interference, or hardware malfunctions at the physical layer can corrupt packets, including their IP headers.
Transmission Errors: During data transmission over networks, especially in wireless or long-distance communications, data can get corrupted due to noise, signal loss, or even due to issues like packet collision.
Faulty Networking Hardware or Software: Sometimes, routers, switches, or even bugs in networking software can cause packet corruption.
Buffer Overflows: If a network device is overwhelmed with too much data, it might result in buffer overflows, leading to corruption.
As for identifying damaged IP headers, here's how it's typically done:
Checksums: IP headers include a checksum field. When a packet arrives, the receiving device recalculates the checksum and compares it with the one in the header. If they don't match, it indicates corruption.
Error-detecting Code: Some network protocols have built-in error detection mechanisms. For instance, Ethernet frames have a frame check sequence (FCS) to detect errors.
Network Tools and Diagnostics: Tools like Wireshark can help analyze network traffic and identify corrupted packets.
Anomalies in Network Performance: Sometimes, signs like increased packet loss rates or unusual network slowdowns can indicate issues with packet corruption.
For references, you might want to check out networking textbooks or authoritative resources like Cisco's networking guides, or academic papers on network reliability and data integrity. They can provide you with more in-depth information and case studies.
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Please elaborate latest Research topics in Networks for Masters level Computer Networks Student?
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Oh, diving into a Masters in Computer Networking? That's awesome! There are some really cool areas you could explore.
Here are a few hot topics:
5G and Beyond: It's all about super-fast internet speeds. Researching how 5G will change the way we connect and its future developments is pretty exciting.
Internet of Things (IoT): Imagine your fridge chatting with your phone! IoT is huge, and studying how to make these connections more secure and efficient is super relevant.
Network Security: With all the cyber threats out there, focusing on how to keep networks safe is like being a digital superhero.
Software-Defined Networking (SDN): This is like giving network administrators superpowers to manage networks with great flexibility and efficiency.
Quantum Networking: It's a bit like sci-fi, but it's real! Exploring how quantum principles can revolutionize data transfer is cutting-edge stuff.
Edge Computing: This is about processing data closer to where it's collected. It’s a big deal for things like self-driving cars.
Artificial Intelligence in Networking: AI can help networks self-repair and optimize. It's a bit like teaching the network to think for itself.
Cloud Networking: With everything moving to the cloud, figuring out how to make this more efficient and secure is a hot topic.
Blockchain in Networking: Beyond cryptocurrencies, blockchain can revolutionize how we secure and manage networks.
Wireless Sensor Networks: These networks are vital for collecting environmental data, and improving their efficiency and data processing can be a great research area.
Pick a topic that excites you the most. It's like choosing your own adventure in the tech world!
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Computer Networking
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Absolutely! When it comes to keeping large computer networks safe and running smoothly, think of it like a well-organized team. Each player has a role:
  1. Encryption: It's like a secret code. Only the intended receiver can understand the information sent over the network.
  2. Firewalls and Intrusion Detection: These are the vigilant goalkeepers, blocking unwanted or harmful traffic.
  3. Network Segmentation and Access Control: Imagine having VIP areas in a network. Only special passes (or permissions) allow access, making it easier to manage and protect.
  4. Regular Updates and Patching: This is like keeping the team’s playbook up-to-date. Fixing vulnerabilities before opponents can exploit them.
  5. Redundancy and Failover: It’s always good to have a backup plan. If one part fails, another takes over without missing a beat.
  6. Backups and Disaster Recovery: Think of it as a safety net. If something goes wrong, you can quickly get back on track.
  7. Monitoring and Analytics: It’s like having a coach who’s always watching the game, ready to spot and react to any unusual plays.
  8. User Education: Everyone on the team needs to know the basics of defense. Training users helps prevent avoidable mistakes.
  9. Physical Security: Don’t forget to lock the doors! Keeping the hardware secure is just as important.
  10. Following Standards and Best Practices: Playing by the rules and learning from the pros always helps the team stay ahead.
Combine all these, and you’ve got a network that’s not just strong in defense, but also reliable in performance. Just like a championship-winning team! 🏆💻
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Dear Doctor
"7 Common Network Security Issues
If your company is aware of the threats listed below, you can create more comprehensive strategies and practices to ensure that your organisation will not fall prey to the cyber world's worst.
1) Internal Security Threats
Over 90% of cyberattacks are caused by human error. This can take the form of phishing attacks, careless decision-making, weak passwords, and more.
Insider actions that negatively impact your business's network and sensitive data can result in downtime, loss of revenue, and disgruntled customers.
2) Distributed Denial-Of-Service (DDoS) Attacks
A DDoS attack causes websites to crash, malfunction, or experience slow loading times. In these cases, cybercriminals infect internet-connected devices (mobile phones, computers, etc.) and convert them into bots. Hackers send the bots to a victim's IP address.
This results in a high volume of internet traffic bombarding the website with requests and causing it to go offline. These attacks make it difficult to separate legitimate and compromised traffic.
3) Rogue Security Software
Rogue security software tricks businesses into believing their IT infrastructure is not operational due to a virus. It usually appears as a warning message sent by a legitimate anti-malware solution.
Once a device is infected with a rogue program, the malware spams the victim with messages, forcing them to pay for a non-existent security solution, which is often malware. Rogue security software can also corrupt your pre-existing cyber security programs to prolong their attack.
4) Malware
Malware are malicious software programs used to gather information about victims through compromised devices. After successful deployments, hackers can mine devices for classified information (email addresses, bank accounts, passwords, etc.) and use them to commit identity theft, blackmail, or other business-damaging actions.
Malware includes:
  • Worms – exploits weaknesses in computer systems to spread to other devices.
  • Rootkits – grants unauthorised access to systems in the form of fraudulent access privilege without the victim's knowledge.
  • Trojan viruses – slips under a network's radar by hitchhiking on other software and provides hackers with unprecedented access to systems.
  • Spyware – gathers information on how devices are used by their owners.
5) Ransomware
Ransomware is a type of malware that encrypts files within infected systems and holds them for ransom, forcing victims to pay for a decryption key to unlock the data. This can take the form of ransomware-as-a-service (RaaS).
RaaS is like software-as-a-service (SaaS), specifically for ransomware. RaaS dealers develop codes that buyers can use to develop their own malware and launch cyberattacks. Some common RaaS examples include BlackMatter, LockBit, DarkSide, and REvil.
6) Phishing Attacks
Phishing attacks are scams where hackers disguise themselves as a trusted entity and attempt to gain access to networks and steal personal information, such as credit card details. Phishing scams take the form of emails, text messages, or phone calls.
Similar to rogue security software, phishing attacks are designed to appear legitimate. This encourages victims to click on malicious links or download malware-laden attachments.
7) Viruses
Computer viruses are commonly attached to downloadable files from emails or websites. Once you open the file, the virus exploits vulnerabilities in your software to infect your computer with malicious code to disrupt network traffic, steal data, and more.
Viruses are not to be confused with worms. Though they both are a type of malware, the difference is in how they penetrate networks. Simply put, computer viruses cannot infect systems until their host (the file) is opened. Worms can infect networks as soon as they enter a business's IT infrastructure."
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Dear Doctor
"Wireless network protocols also have some drawbacks, such as interference, latency, bandwidth, and range limitations. Wireless signals can be affected by physical obstacles, electromagnetic noise, or other wireless devices, resulting in lower quality or loss of connection. Wireless network protocols also have higher latency than wired networks, meaning they take longer to send and receive data. Wireless network protocols also have limited bandwidth, meaning they can only support a certain amount of data at a time. Wireless network protocols also have limited range, meaning they can only cover a certain distance from the source."
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I want to implement various WSN attacks and then to analyze network performance. Is there any WSN attack simulator available. How can we implement WSN attacks 
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You can see this post which explains the impact of DDOS attacks on the performance of a WSN network https://support.tetcos.com/a/solutions/articles/14000141596
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What is the last research areas for 2023
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As an AI language model, I cannot predict the future or provide a definitive list of the top research areas for computer networks in 2023. However, based on current trends and developments in the field, here are ten potential research areas that could be of interest in the near future:
  1. 5G and beyond: The development of 5G networks is ongoing, and research in this area is likely to continue as 5G deployment expands globally. In addition, research into future generations of wireless networks beyond 5G, such as 6G, may also be a focus.
  2. Edge computing: As more devices are connected to the Internet of Things (IoT), edge computing has become increasingly important. Research into optimizing network performance at the edge and security and privacy concerns is likely to continue.
  3. Software-defined networking (SDN): SDN has the potential to improve network management, reduce costs, and increase flexibility. Research in this area will likely focus on improving performance, scalability, and security.
  4. Network virtualization: Network virtualization allows multiple virtual networks to run on a single physical network, improving resource utilization and flexibility. Research in this area may focus on optimizing virtual network performance and improving security.
  5. Network function virtualization (NFV): NFV involves virtualizing network functions, such as firewalls and load balancers, and running them on commodity hardware. Research in this area may focus on improving NFV performance, scalability, and security.
  6. Cloud computing: Cloud computing has transformed how networks are managed and deployed. Research in this area may focus on improving cloud performance, scalability, and security and addressing privacy concerns.
  7. Artificial intelligence (AI) and machine learning (ML): AI and ML can potentially improve network performance and security. Research in this area may focus on developing new algorithms and techniques for network optimization, anomaly detection, and threat detection.
  8. Quantum networking: Quantum networking has the potential to provide unprecedented levels of security and privacy. Research in this area may focus on developing new protocols and technologies for quantum key distribution and other quantum-based network applications.
  9. Blockchain-based networking: Blockchain technology has the potential to provide secure and decentralized networking. Research in this area may focus on developing new protocols and applications for blockchain-based networking.
  10. Network security: As networks become more complex and cyber threats become more sophisticated, research into network security will likely continue to be a high priority. Areas of focus may include threat detection, intrusion prevention, and incident response.
It's important to note that these are just potential areas of research and are not a definitive list of the top research areas for computer networks in 2023. The field of computer networks is constantly evolving, and new developments and challenges may arise that require research and innovation in other areas.
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I am conducting some research on computer networks, and I want to simulate different types of network links. For example, 5G networks, Fibre networks, etc. Is there any resource where I can find the link conditions, such as the bandwidths, latencies, and loss of each link?
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There are traditional Network Simulators like NS3 OMNET++, Opnet and NETSIM. Check this out too
Also Emulators are worth looking into (not just simulators) like MININET and Shadow (https://shadow.github.io)
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I have to simulate DCCP and UDP on NS2 , for my presentation and showing the differences in throughput, delay, and jitter. I want to know that NS 2.35 standalone supports DCCP simulation, do I have to write any code for this simulation?
I am new to NS2 n linux platform.
Help is appreciated.
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Fedora or Ubuntu both work well with NS
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I am working on cyber security domain. Currently, the work is to trace out the real ip address behind the VPN.
1. Is there any technique or api to trace out the real ip address which is masked with VPN?
2. How to determine whether the input ip address is original/proxy/vpn without any api support?
Researchers, Kindly provide the suggestion for the above questions.
#cybersecurity #vpn #proxy #networksecurity #researcher
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It's great if you can explain how to identify those issues as well.
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HTTPS://securityinstitute.com/netanalyst has retro free videos on Ethernet, Switches and Routing. The videos were part of NetAnalyst Network Forensic Certification I created and trained 50k and certified 3,500 professionals in 27 countries.
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I need a security dataset with challenges, I mean I want the accuracy to be low so that I can enhance it using ML techniques. I tried several datasets but they already have high accuracy without enhancement.
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Mohamed Amine Ferrag, Othmane Friha, Djallel Hamouda, Leandros Maglaras, Helge Janicke, "Edge-IIoTset: A New Comprehensive Realistic Cyber Security Dataset of IoT and IIoT Applications for Centralized and Federated Learning", IEEE Access, April 2022, DOI: 10.1109/ACCESS.2022.3165809
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If you can provide references if possible, that will be a great help.
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David Lide Yeah but what are the protocols used to read those data. For an example FLPs are used to do auto negotiation. Like wise how are the other things are read or managed by the NIC?
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I am a PhD student in computer science, and I want to apply reinforcement learning methods to computer network problems and get results in order to publish a research paper in international journals, but I am not very good in mathematics, so my question is: can I model a problem and apply reinforcement learning to problems without needing mathematics?
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Mathematics is like the backbone to Reinforcement Learning. Strong command on topics like Probability and Statistics with a proper understanding of some mathematical models can take you very far ahead in Reinforcement Learning. Some scheduling techniques in wireless packet delivery require deep knowledge of Markov chain, Deep Reinforcement Learning.
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Would you please suggest to me a Q1 or Q2 subscription journal (without any publishing fee) in various areas of computer networks and the Internet of Things with a fast-processing time and no limit to publishing the number of free pages (unlike IEEE IoT, IEEE Systems, IEEE Sensors, etc.)? Unfortunately, journals such as Computer Networks, Computer Communications, and FGCS have slowed down a lot in the last year or two, especially in the process of initial review by editors and assignment of reviewers.
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Ali Seyfollahi Check out ACM Transactions on Sensor Networks too (TOSN).
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I have created a new packet header in NS2 which contains two fields.Is there any way to check to see if the packet header fields contains the value I have given through tcl.
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How to add value in packet header in VANET using NS2 wireless
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Mechanisms leading to the spastic movement disorder (SMD) as a positive symptom of the upper motor neuron syndrome are not yet fully understood. All, the underlying disease, the (spinal) lesion level, the lesion location within the brain, affected descending (parapyramidal) motor tracts, disrupted sensory input etc. seem to be more or less relevant for the emergence of a SMD.
Is there any research on computational network models of spinal/supraspinal spasticity on the base of current neuroanatomical and neurophysiological data known to be of relevance for the develoement of a spastic movement disorder?
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See Project:
"A Computational Model for Epidural Electrical Stimulation of Spinal Sensorimotor Circuits "
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Recently I am looking for SDN issues, but still no idea which issues should focus.
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Thank you so much for your suggestion and sharing
Jehad Ali
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I'm a computer network undergraduate who is looking for an idea to do my final year project. Can anyone give your suggestions?
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You can explore intrusion detection in computer networks. Machine learning algorithms may assist you greatly in this.
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Please help me with the following formulation.
I want to calculate transmit power that can satisfy a given SINR threshold on the receiver side.
My formulation is as follows:
SINR=Received_Power/(Interference+Noise) Eq. 1
If SINR Threshold (SINR_th) is known, we can get the Required_Received_Power and thus the "Required_Transmit_Power" power as follows:
SINR_th=Required_Received_Power/(Interference+Noise) Eq. 2
We know that
Received_Power=Transmit_Power/Pathloss; Eq. 3
OR
Required_Received_Power=Required_Transmit_Power/Pathloss; Eq. 4
Substituing "Required_Received_Power" in Eq.2 with the right hand side of Eq.4, we get
SINR_th=(Required_Transmit_Power/Pathloss)/(Interference+Noise) Eq. 5
OR
Required_Transmit_Power=SINR_th x (Interference+Noise) x Pathloss Eq. 6
Please advise whether this formulation is correct or not as I am getting wrong results.
Thank you!!!
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Muhammad Hamza El-Saba Thank you very much for your answer.
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I am looking for latest research topics in the field of LISP protocol. I am doing master's in computer networks and now want to research in LISP protocol. Please guide me regarding this.
Thank you
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Latest work on LISP till 2 years ago was related to blockchain support using LISP control plane. https://ieeexplore.ieee.org/abstract/document/8761995. you could contact the authors for further guidance. Basically, due to the separation of location and identity, LISP can we used for enhancing privacy.
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Hello and Happy new year , I am currently searching a topic for my thesis. I study Computer Science with netwotks specialization . I am looking for a topic which maintains a balance between theoretical and practical-experimental research . The stuff I would like to be included, are: C, Java , NS2 , Matlab, signal processing, Packet tracer, general network management and I would like to learn a modern skill which will be usefull in a future job. Thank you in advance.
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below few topics for master thesis in computer networks
•Investigate bandwidth measurement techniques that require low overhead, few probing messages, and good estimation results of bottleneck and available bandwidth.
•The research can be based on Modified Bprobe, Cprobe, Aprobe, pathchar, ping, traceroute tools.
•The techniques are critical in server/ISP selection, billing, network control, network monitoring, and real-time streaming applications.
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i am working on research about mobility aware service migration in fog computing network. i dont know how to use genetic algorithm? and how can i convert it into matlab code?
i need to know if there are other any available tools? how can i simulate genetic algorithm?
how can i relate between it and iFOGSIM environment?
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I'm also having similar issue. I want to Integrate an ACO algorithm developed in Matlab with iFogSim. Anyone with an idea of how this could be a achieved?
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I am using the abbrvnat style, but I want the label to appear next to each reference. For example, I want to have:
[Atzori et al., 2010] L. Atzori, A. Iera, and G. Morabito. The Internet of Things: A Survey. Computer networks, 54(15):2787-2805, 2010.
Instead of :
L. Atzori, A. Iera, and G. Morabito. The Internet of Things: A Survey. Computer networks, 54(15):2787-2805, 2010.
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I want to create wireless nodes and simulate a communication between them.
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Can see the demo in wireless communication by using a helper function
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Who did work in Complex computer network optimization problems?
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two main things:
- Links or nodes subject to failure
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internet of things
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It is base on the Internet.
Kindly, you can click the link below to find a complete, new, and full answer:
Or refer to this:
Nidhal Kamel Taha El-Omari, “Cloud IoT as a Crucial Enabler: a Survey and Taxonomy”, Modern Applied Science, The Canadian Center of Science and Education, published by Canadian Center of Science and Education, Canada, p-ISSN: 1913-1844, e-ISSN: 1913-1852, DOI:10.5539/mas.v13n8p86, 13(8):86-149, 2019.
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Computer network is a group of computers that use a set of common communication protocols over digital interconnections for the purpose of sharing resources located on or provided by the network nodes.
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Dear Md Adil
Your question is like saying how necessary is air for humans?
Anyway, computer networks have organized to make the world a small village.
regatds
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I understand that CAN is a serial communication protocol where there is not source authentication. This itself brings a lot of troubles, but what else is missing?  
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Due to the depletion of the global IPv4 address pool, some new Internet clients will not be able to get IPv4 adresses, but only IPv6 addresses. However the majority of the internet still uses IPv4 addresses. The IPv6 only clients should be able to communicate with the IPv4 only servers. For this problem, the combination of the DNS64 (RFC 6147) and NAT64 (RFC 6146) is a good solution.
We test different free software (also called open source) DNS64 and NAT implementations. As for DNS64, we tested BIND and TOTD.
(For our results, see: Gabor Lencse, Sandor Repas, "Performance Analysis and Comparison of Different DNS64 Implementations for Linux, OpenBSD and FreeBSD," aina, pp.877-884, 2013 IEEE 27th International Conference on Advanced Information Networking and Applications (AINA), 2013)
Besides these, we know also the PowerDNS and Unbound.
Can someone suggest other free software for DNS64 implementations?
Had anyone tested their performance and/or stability?
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Dear Colleagues:
Below is the up to date feasibility demonstration that you may like to have a look at.
Abe (2020-08-29 12:13 EDT)
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I want to simulate Bcube,porland topology with NS-3 simulator,but I don't know how can I start point and don't know if it's feasible. If someone did it,please tell me.Thanks a lot.
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Hi colleague
Nutshell as Simulation Toolkit for Modeling Data Center Networks and Cloud Computing...
Find the following URL may help you:
Regards....
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I want to undergo the traning programme on Simulation for Wireless Sensor Netowks.
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I am using the omnet++ as simulators network for vanet by using veins so how do I implement a new routing protocol for veins where use 802.11p.
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Liang zhao did you figure out how to implement routing protocols in veins ?
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Dear Concern,
I need a kind help from u that is your guidance to publish a book by a good publisher.
i have prepared the complete Contents you can visit on www.nripesheschool.com
i want to publish two books
1. Fundamental of PHP and MYSQL
2. Fundamental of Computer Networks
Kindly guide me for the same.
Regards.
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Publish your book at respectful publishers like Springer, Elsevier, Sage, Emerald.
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how can i measure the "average received CNR(carrier-to-noise ratio)" which is given by Mohamed-Slim Alouini and Andren Goldsmith in "capacity of nakagami multipath fading channels". We all know that we can measure the recieved CNR by transmitted CNR- channel loss. Can i calculate the average received CNR in the same way average received CNR= average transmitted CNR-loss? I mean do the average CNR for transmitter and the receiver have the relation that can be used in the received CNR and transmitted CNR? ill appreciate it for ur answers
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C/N = 20 log 10 [Vc/ Vn]
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I am planning to do a dissertation on intrusion prevention system. Can anyone give suggestion on how to develop one from scratch? Like what are the things that I should look upon. I have a fair idea of computer networks. I'm very much interested in information security, network security. Please provide me some intuitive and simple ways to understand the system and implement the same.
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If you want to develop one you can do it using python. There are many tutorials on youtube that shows how to develop one from scratch.
ex - Udemy - Learn Python & Ethical Hacking From Scratch
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Any suggestions on how to parse such large pcap.gz files of telescope data from caida.
If I use tcpdump or tshark, it is taking too long to parse them.
Also, I have a big list of filter prefixes, tcpdump throws an error of too long filter file. How to take care of that?
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Follow
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There are several ways to do this. Install reliable and updated anti-virus program on all computers. Make sure firewalls are setup and configured properly. Researchers, What are the best deeper options to handle this security and management?
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Securing your network can be done in different ways, without going in details (you can look up the different terms yourself).
Hardening network (use firewalls / IPS), implement segmentation (subnetting), Update software, Monitoring (NIDS, HIDS, read logging).
Check list: - change standard passwords - remove unused users & guest - remove unneeded services (f.e.Wi-Fi, bluetooth) - block unneeded ports - update software (on network devices like routers, firewalls etc) - use smart firewall settings to enable the needed services and block unwanted traffic. Last but not least test your network by periodic pentesting.
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Topic: Viral marketing in social network, data mining, influence maximization, computer network, big data, network optimization, influence maximization
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Elsevier list, go to View More on Journal Insights, it shows the list of information like, Review Speed, impact factor. See the Review speed and submit article based on review speed.
Hope this would be helpful.
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I am planning to do a dissertation on intrusion prevention system. Can anyone give suggestion on how to develop one from scratch? Like what are the things that I should look upon. I have a fair idea of computer networks. I'm very much interested in information security, network security. Please provide me some intuitive and simple ways to understand the system and implement the same.
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go through this link ...it will give you better idea
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I am looking for dataset related to network devices such as routers, switches, servers and access points In performing network prediction
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Hi,
A application concerns the problem of predicting the size of a flow and ... to improve routing, load balancing and scheduling in computer networks. ... process regression and online Bayesian Moment Matching on three datasets of real traffic.
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I am working on trust computation using machine learning techniques in matlab. Can someone provide me with the code on recommendation attacks to that I can apply machine learning techniques in detect the malicious activities in VANET
Thanks 
Elvin
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I am working on VANET Project and I am looking for Matal coding so please help me out
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I am working on a project to compare Software Defined network and conventional network using performance metrics such as throughput, delay, and latency; but I have not been able to use OPNET Modeller to simulate the OpenFlow SDN. I need help and if possible an instructor regarding this.
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How can make security settings for APS in opnet project
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Vertical Handover (VHO) decision algorithm for heterogeneous network architectures which integrate both cellular networks and Wireless Local Area Networks (WLANs). The cellular-WLAN and WLAN-WLAN VHO decisions are taken based on parameters which characterize both the coverage and the traffic load of the WLANs. Both HHO and VHO processes consist of three steps: handover requirement estimation, target network selection and handover execution [8]. Networks such as LTE, WLAN and WiMAX provide multiple choices for network access. Moreover, roaming terminals are equipped with multiple radio interfaces for heterogeneous wireless network access. Handoff Decision is very crucial process because it will be helpful in determining when and where to perform handoff and to select the best network in the Heterogeneous environment without any degradation in the performance.
Papers:
Obayiuwana, E. and Falowo, O.E., 2017. Network selection in heterogeneous wireless networks using multicriteria decision-making algorithms: a review. Wireless Networks, 23(8), pp.2617-2649.
Ndashimye, E., Ray, S.K., Sarkar, N.I. and Gutiérrez, J.A., 2017. Vehicle-to-infrastructure communication over multi-tier heterogeneous networks: a survey. Computer Networks, 112, pp.144-166.
Obayiuwana, E. and Falowo, O.E., 2017. Network selection in heterogeneous wireless networks using multicriteria decision-making algorithms: a review. Wireless Networks, 23(8), pp.2617-2649.
Sarkar, S.K., Basavaraju, T.G. and Puttamadappa, C., 2016. Ad hoc mobile wireless networks: principles, protocols, and applications. CRC Press.
Baghla, S. and Bansal, S., 2014, November. Performance of VIKOR MADM method for Vertical Handoffs in Heterogeneous networks with various weighting methods. In 8th International Conference on Advanced Computing and Communication Technologies ICACCT 2014 (pp. 29-34).
Omheni, N., Zarai, F., Obaidat, M.S., Smaoui, I. and Kamoun, L., 2014. A MIH-based approach for best network selection in heterogeneous wireless networks. Journal of Systems and Software, 92, pp.143-156.
Bhosale, S. and Daruwala, R., 2014. Multi-criteria Vertical Handoff Decision Algorithm Using Hierarchy Modeling and Additive Weighting in an Integrated WLAN/WiMAX/UMTS Environment-A Case Study. KSII Transactions on Internet & Information Systems, 8(1).
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The most recent advances and standard performance assessment metrics for efficient vertical handoff in heterogeneous network by CEAM Protocol are
From an architecture perspective, the HetNet can be viewed as encompassing conventional macro radio access network (RAN) functions, RAN transport capability, small cells and Wi-Fi functionality, that are increasingly being virtualized and delivered in an operational environment where span of control includes data center resources associated with compute, networking and storage.
In this framework, self-optimizing network (SON) functionality is essential to enable order-of-magnitude network densification with small cells. Self-configuration or ‘plug and play’ reduces time and cost of deployment, while self-optimization then ensures the network auto-tunes itself for maximum efficiency as conditions change. Traffic demand, user movements and service mix will all evolve over time, and the network needs to adapt to keep pace. These enhanced SON capabilities will therefore need to take into account the evolving user needs, business goals and subscriber behaviours.
Importantly, functions associated with HetNet operations and management take earlier SON capability that may have only been targeted at a single domain and/or technology, and expand it to deliver automated service quality management across the entire HetNet.
Wireless
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computer networks
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yes, in the hubs.
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There is a way to model computer networks (in terms of latency, bandwidth, packet size, etc.) through (stochastic?temporized?) automata? If I look for networked automata, I only find automata about "local" network of interacting components (e.g., cells)
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An interesting question. I am glad that interesting reflections, responses and conclusions have emerged that may be an inspiration to continue research in this area. Therefore, I am still reading the answers, following the interesting discussion. Best wishes
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As we know that, throughput is amount of transferred data for a specific time. I want to fix data size and make time variable. The definition will be "The amount of time required to transfer a specific amount of data". What is the term for this?
Thanks in advance.
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Dear Anik Islam Abhi,
this is "transfer / transmission time". I would use the following terms:
Transmission over a data link: transmission time; packet / data transmission time; (mean) packet / data transmission time
(mean => variable packet / data length)
When transmission over multiple data links (delays in nodes) I would use the terms: transfer time; packet/data transfer time; (mean) packet/data transfer time
Best regards
Anatol Badach
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Dears;
Pleas to provide a simple manner to decrease the network latency as soon as possible for quick paper printing response in the university computer lab.
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Thanks dear Robert Mahar ;
very good information...
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Which simulation tool is better for implementing a secure routing protocol in Wireless Sensor Networks Ns3 or Omnet++?
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i thind omnet++ is a better choice.
its flexible and support every thing you want.
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Hi,
I am looking for journals with good impact factor that cover the scope of modern technology impact (e.g. computers or computer networks) on saving the environment.
regards.
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Dear Salim,
these journals might be suitable:
IEEE Internet of Things Journal,
Sensors — Open Access Journal
Journal of Sensors,
IEEE Internet of Things Journal,
Journal of Sensor and Actuator Networks,
EURASIP Journal on Wireless Communications and Networking.
See also the list of journals A-Z:
Best regards
Anatol Badach
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I wanted to know which are the network simulators related to development of security protocols where the simulation codes can directly be implemented into hardware!! all suggestions are welcome.
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For me, I suggest to use Cisco Packet Tracer if you want to create a simulation much comparable to reality. But If you are looking forward to develop an algorithm, I suggest you follow another software.
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I know NS and GloMoSim for Ad-hoc networks. Is there a simulator used for home networks?
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Defiantly, Cisco Packet Tracer is very good solution for Home Networks
You can checkout the following tutorials:
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I need to prepare a presentation on a base paper (>2015) in Computer Networks for my class work. I also need to implement the paper. The problem is, I am kind of a beginner in CN. So, I am not able to select a topic which I can understand completely (especially the math). Can someone help me out with a topic which is relatively recent and also takes my personal contraints into consideration ?
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IPv6 for IoT
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i want to work on game theory so i want to know the recent work on this topic
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Dear Saifullah Khan,
One of the most popular and entertaining topics in game theory is the
( Life and death game of John Conway) based on cellular automaton.
Best regards
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Hello researchers,
Related to your research/experience field, what are the technologies you simulate often and you can judge that this task is complicated, tedious, or time consuming ?
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"How do we can detect in advance, that the Mobile Node will detach from the first subnet to another subnet within the same domain ? i.e the mechanism?"
"In Distributed Mobility Architecture, for example in Distributed PMIPv6, how do we detect that the MN will detach from MAG1 to MAG2 in advance?"
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Sci journal
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Modern physic letter A -world scientific Visual computer Springer
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Does anyone have experience with FIREMAN toolkit. I need to know how to install it, and how to use it to analyse the efficiency of my firewall?
Or, what tools you using to analyse and test the efficiency of your Firewall?
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No idea till now
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Do Cloud security framework and also cloud advanced database using nodejs and Angularjs
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Vehicaular Adhoc Network Routing Simulation
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What is relation between Machine Intelligence and Smart Networks?
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Artificial Intelligence has been around for a long time – the Greek myths contain stories of mechanical men designed to mimic our own behavior. Very early European computers were conceived as “logical machines” and by reproducing capabilities such as basic arithmetic and memory, engineers saw their job, fundamentally, as attempting to create mechanical brains.
As technology, and, importantly, our understanding of how our minds work, has progressed, our concept of what constitutes AI has changed. Rather than increasingly complex calculations, work in the field of AI concentrated on mimicking human decision making processes and carrying out tasks in ever more human ways.
Artificial Intelligences – devices designed to act intelligently – are often classified into one of two fundamental groups – applied or general. Applied AI is far more common – systems designed to intelligently trade stocks and shares, or manoeuvre an autonomous vehicle would fall into this category.
Neural Networks – Artificial Intelligence And Machine [+]
Generalized AIs – systems or devices which can in theory handle any task – are less common, but this is where some of the most exciting advancements are happening today. It is also the area that has led to the development of Machine Learning. Often referred to as a subset of AI, it’s really more accurate to think of it as the current state-of-the-art.
The Rise of Machine Learning
Two important breakthroughs led to the emergence of Machine Learning as the vehicle which is driving AI development forward with the speed it currently has.
One of these was the realization – credited to Arthur Samuel in 1959 – that rather than teaching computers everything they need to know about the world and how to carry out tasks, it might be possible to teach them to learn for themselves.
The second, more recently, was the emergence of the internet, and the huge increase in the amount of digital information being generated, stored, and made available for analysis.
Once these innovations were in place, engineers realized that rather than teaching computers and machines how to do everything, it would be far more efficient to code them to think like human beings, and then plug them into the internet to give them access to all of the information in the world.
Neural Networks
The development of neural networks has been key to teaching computers to think and understand the world in the way we do, while retaining the innate advantages they hold over us such as speed, accuracy and lack of bias.
A Neural Network is a computer system designed to work by classifying information in the same way a human brain does. It can be taught to recognize, for example, images, and classify them according to elements they contain.
Essentially it works on a system of probability – based on data fed to it, it is able to make statements, decisions or predictions with a degree of certainty. The addition of a feedback loop enables “learning” – by sensing or being told whether its decisions are right or wrong, it modifies the approach it takes in the future.
Machine Learning applications can read text and work out whether the person who wrote it is making a complaint or offering congratulations. They can also listen to a piece of music, decide whether it is likely to make someone happy or sad, and find other pieces of music to match the mood. In some cases, they can even compose their own music expressing the same themes, or which they know is likely to be appreciated by the admirers of the original piece.
These are all possibilities offered by systems based around ML and neural networks. Thanks in no small part to science fiction, the idea has also emerged that we should be able to communicate and interact with electronic devices and digital information, as naturally as we would with another human being. To this end, another field of AI – Natural Language Processing (NLP) – has become a source of hugely exciting innovation in recent years, and one which is heavily reliant on ML.
NLP applications attempt to understand natural human communication, either written or spoken, and communicate in return with us using similar, natural language. ML is used here to help machines understand the vast nuances in human language, and to learn to respond in a way that a particular audience is likely to comprehend.
A Case Of Branding?
Artificial Intelligence – and in particular today ML certainly has a lot to offer. With its promise of automating mundane tasks as well as offering creative insight, industries in every sector from banking to healthcare and manufacturing are reaping the benefits. So, it’s important to bear in mind that AI and ML are something else … they are products which are being sold – consistently, and lucratively.
Machine Learning has certainly been seized as an opportunity by marketers. After AI has been around for so long, it’s possible that it started to be seen as something that’s in some way “old hat” even before its potential has ever truly been achieved. There have been a few false starts along the road to the “AI revolution”, and the term Machine Learning certainly gives marketers something new, shiny and, importantly, firmly grounded in the here-and-now, to offer.
The fact that we will eventually develop human-like AI has often been treated as something of an inevitability by technologists. Certainly, today we are closer than ever and we are moving towards that goal with increasing speed. Much of the exciting progress that we have seen in recent years is thanks to the fundamental changes in how we envisage AI working, which have been brought about by ML. I hope this piece has helped a few people understand the distinction between AI and ML. In my next piece on this subject I go deeper – literally – as I explain the theories behind another trending buzzword – Deep Learning.
Bernard Marr is a best-selling author & keynote speaker on business, technology and bigdata. His new book is Data Strategy. Toread hisfuture posts simply join his network here.
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Could anyone provide me examples of research opportunities in Cloud Computing and Network Functions Virtualization (NFV) together?
How could I work or conduct experiments using both?
Articles are also welcome.
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Dear Emanuel Coutinho,
the two concepts of cloud computing (CC) and NFV complement each other ideally and have an important significance for the IoT. The integration of CC and NFV in the IoT allows to create a variety of interesting new IoT services. In IoT, virtualized network features (that is, NFV instances) can be provided as a kind of mini-clouds (or micro-clouds). Mini-clouds in the IoT enable the realization of widely distributed and time-critical IoT services. In this case we speak of fog computing. Mini-Clouds (as NFV instances) can also be located in WSNs, this means at the edge of the Internet (in so-called endge components). This means edge computing.
The NFV instances provide intelligence. This intelligence makes it possible to realize a new type of computing, so-called cognitive computing, both in mini-clouds (Fog Computing) and in edge components (Edge Computing). This is especially important in the IoRT (Internet of Robotic Things).
Of great importance is the integration of SDN (Software Defined Networking) and NFV for the IoT. An SDN controller can be realized in a cloud. If a hierarchical structure of SDN controllers is required, this structure can be set up as a cloud hierarchy. The SDN switches can be implemented as NFV instances and provided as clouds. Consequently, one type of integration CC and NFV is the integration of SDN and NFV.
For the future container networking, the integration of SDN and NFV (in fact the integration CC and NFV) is of great importance. With Container Networking, the NFV instances can be transported in containers. Multiple distributed NFV instances can be orchestrated using SDN controllers. New Internet of Vehicles (IoV) services can be provided through container networking and orchestration of NFV mobile instances in Cluods and / or Mini Clouds (Fog). In this way, various IoV services can be organized to support autonomous driving.
When integrating CC and NFV, the concept of SFC (Service Function Chaining) can play an important role.
The literature sources listed here show some of these ideas.
Good luck and best regards
Anatol Badach
SDN/NFV-based Internet-of-Things
Orchestration of IoT Services
SDN-based IoT Framework with NFV Implementation
A SDN-IoT Architecture with NFV Implementation
A Software-Defined Approach for End-to-end IoT Networking
Container Network Functions
For the basic ideas of SDN, NFV and SFC see:
For SDN the figures 005455, 5466 and 5458 in:
For NFV the figures 007012, 7013 and 7017 in:
For SFC the figures 007101, 7102, 7103, 7105 and 7107 in: