Iqbal H. Sarker

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Verified

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• PhD in Computer Science (Australia)
• Research Fellow at Edith Cowan University

Due to the advanced features in recent smartphones and context-awareness in mobile technologies, users’ diverse behavioral activities with their phones and associated contexts are recorded through the device logs. Behavioral patterns of smartphone users may vary greatly between individuals in different contexts—for example, temporal, spatial, or so...

This paper formulates the problem of a rule-based machine learning method to discover the behavioral rules of individual smartphone users to provide context-aware intelligent services. Smartphones nowadays are considered as one of the most important Internet-of-Things (IoT) devices for providing various context-aware personalized services. These de...

In the current age of the Fourth Industrial Revolution (4IR or Industry 4.0), the digital world has a wealth of data, such as Internet of Things (IoT) data, cybersecurity data, mobile data, business data, social media data, health data, etc. To intelligently analyze these data and develop the corresponding smart and automated applications, the know...

Critical infrastructure (CI) typically refers to the essential physical and virtual systems, assets, and services that are vital for the functioning and well-being of a society, economy, or nation. However, the rapid proliferation and dynamism of today’s cyber threats in digital environments may disrupt CI functionalities, which would have a debili...

Critical National Infrastructures (CNIs)—including energy grids, water systems, transportation networks, and communication frameworks—are essential to modern society yet face escalating cybersecurity threats. This review paper comprehensively analyzes AI-driven approaches for Critical Infrastructure Protection (CIP). We begin by examining the relia...

Large Language Models (LLMs) such as ChatGPT and GitHub Copilot have revolutionized automated code generation in software engineering. However, as these models are increasingly utilized for software development, concerns have arisen regarding the security and quality of the generated code. These concerns stem from LLMs being primarily trained on pu...

Cybersecurity has become a major concern in the modern world due to our heavy reliance on cyber systems. Advanced automated systems utilize many sensors for intelligent decision-making, and any malicious activity of these sensors could potentially lead to a system-wide collapse. To ensure safety and security, it is essential to have a reliable syst...

Large language models (LLMs) are an exciting breakthrough in the rapidly growing field of artificial intelligence (AI), offering unparalleled potential in a variety of application domains such as finance, business, healthcare, cybersecurity, and so on. However, concerns regarding their trustworthiness and ethical implications have become increasing...

Cyber scammers frequently use PDF (Portable Document Format) files to install malicious code and infect consumers' systems. Standard remedies and techniques for identifying adversarial PDF malware are often insufficient to stop it completely. This is because adversarial PDF malware is flexible and doesn't depend on a single set of features. Therefo...

COVID-19 is an infectious respiratory disease that has had a significant impact, resulting in a range of outcomes including recovery, continued health issues, and the loss of life. Among those who have recovered, many experience negative health effects, particularly influenced by demographic factors such as gender and age, as well as physiological...

Phishing and spam have been a cybersecurity threat with the majority of breaches resulting from these types of social engineering attacks. Therefore, detection has been a long‐standing challenge for both academic and industry researcher. New and innovative approaches are required to keep up with the growing sophistication of threat actors. One such...

In assisted living facilities or nursing homes, residents’ movements or actions can be monitored using Human Activity Recognition (HAR), ensuring they receive proper care and attention. The significance of HAR is substantial in reviewing and updating emergency response plans to address unusual behavior patterns of individuals in the context of dail...

Large Language Models (LLMs) are an exciting breakthrough in the rapidly growing field of artificial intelligence (AI), offering unparalleled potential in a variety of application domains such as finance, business, healthcare, cybersecurity, and so on. However, concerns regarding their trustworthiness and ethical implications have become increasing...

In the contemporary digital age, social media platforms like Facebook, Twitter, and YouTube serve as vital channels for individuals to express ideas and connect with others. Despite fostering increased connectivity, these platforms have inadvertently given rise to negative behaviors, particularly cyberbullying. While extensive research has been con...

The integration of cybersecurity and artificial intelligence (AI), referred to as “CyberAI,” represents a dynamic and transformative landscape. This chapter outlines the diverse landscape of AI variants, as well as their diverse real-world applications in bolstering cybersecurity. The discourse explores the importance of explainable AI and emphasiz...

In a computing context, cybersecurity technology and operations are constantly changing, and data science is driving the change. Building a data-driven model that extracts patterns in cybersecurity incidents is the key to automating and intelligently managing a security system. This chapter mainly explores the convergence of cybersecurity and data...

This chapter explores the transformative landscape of learning technologies, focusing specifically on machine learning and deep learning techniques used in cybersecurity. As digital threats become increasingly sophisticated and complex, conventional cybersecurity approaches are becoming inadequate. The chapter explores how machine learning and deep...

With the convergence of artificial intelligence (AI) and cybersecurity, a new paradigm has emerged in how we defend against evolving digital threats. This book explores the dynamic landscape of AI-driven cybersecurity and threat intelligence, emphasizing how the computing and analytical power and decision-making capabilities of AI technologies are...

Cybersecurity is encountering new challenges demanding innovative solutions due to the complexity and frequency of cyberattacks progressing. Artificial intelligence (AI), particularly generative AI, has emerged as a promising technology with the potential to revolutionize current cybersecurity modeling and practices. This chapter provides a compreh...

This chapter explores how artificial intelligence (AI) can be used to enhance the protection and resilience of critical infrastructure. Society is becoming increasingly dependent on interconnected systems, which makes critical infrastructure more vulnerable to cyber threats and other risks. In this chapter, AI technologies are strategically integra...

Detecting cyber-anomalies and attacks are becoming a rising concern these days in the domain of cybersecurity. The knowledge of artificial intelligence (AI), particularly the machine learning techniques, can be used to tackle these issues. However, the effectiveness of a learning-based security model may vary depending on the security features and...

AI-driven cybersecurity is crucial to enhancing the resilience of the Internet of Things (IoT) and smart city ecosystems. Due to the dynamic and heterogeneous nature of IoT devices, these interconnected networks have become an integral part of urban infrastructure. Using artificial intelligence, particularly machine learning algorithms, enables pro...

This chapter provides a foundational understanding of cybersecurity concepts, including terminologies and attack frameworks like the cyber kill chain and MITRE ATT&CK, as well as the cybersecurity life cycle. In this chapter, key terms regarding threats, vulnerabilities, security controls, and relevant emerging technologies associated with AI are c...

In today’s industrial environments, advanced technologies have become increasingly integrated, increasing vulnerabilities and risks related to cyber threats. This chapter explores the transformative role of artificial intelligence (AI) in enhancing the security of industrial control systems (ICS) and operational technology (OT) environments. Increa...

Bangladesh is predominantly an agricultural country, where the agrarian sector plays an essential role in accelerating economic growth and enabling the food security of the people. The performance of this sector has an overwhelming impact on the primary macroeconomic objectives like food security, employment generation, poverty alleviation, human r...

People may now receive and share information more quickly and easily than ever due to the widespread use of mobile networked devices. However, this can occasionally lead to the spread of false information. Such information is being disseminated widely, which may cause people to make incorrect decisions about potentially crucial topics. This occurre...

As cyber threats evolve and grow progressively more sophisticated, cyber security is becoming a more significant concern in today’s digital era. Traditional security measures tend to be insufficient to defend against these persistent and dynamic threats because they are mainly intuitional. One of the most promising ways to handle this ongoing probl...

The Portable Document Format (PDF) is one of the most widely used file types, thus fraudsters insert harmful code into victims’ PDF documents to compromise their equipment. Conventional solutions and identification techniques are often insufficient and may only partially prevent PDF malware because of their versatile character and excessive depende...

Cervical cancer is a significant contributor to female mortality on a global scale, especially in low-income countries where effective screening programs for the detection and treatment of precancerous conditions are lacking. Classification of pap-smear test cervical cell images is crucial as it gives essential information for the diagnosis of mali...

Managing the System Development Lifecycle (SDLC) is a complex task because of its involvement in coordinating diverse activities, stakeholders, and resources while ensuring project goals are met efficiently. The complex nature of the SDLC process leaves plenty of scope for human error, which impacts the overall business cost. This paper introduces...

Phishing and spam detection is a long standing challenge that has been the subject of much academic research. Large Language Models (LLM) have vast potential to transform society and provide new and innovative approaches to solve well-established challenges. Phishing and spam have caused financial hardships and lost time and resources to email user...

This position paper explores the broad landscape of AI potentiality in the context of cybersecurity, with a particular emphasis on its possible risk factors with awareness, which can be managed by incorporating human experts in the loop, i.e., "Human-AI" teaming. As artificial intelligence (AI) technologies advance, they will provide unparalleled o...

Cyber risk refers to the risk of defacing reputation, monetary losses, or disruption of an organization or individuals, and this situation usually occurs by the unconscious use of cyber systems. The cyber risk is unhurriedly increasing day by day and it is right now a global threat. Developing countries like Bangladesh face major cyber risk challen...

Age estimation from facial images has gained significant attention due to its practical applications such as public security. However, one of the major challenges faced in this field is the limited availability of comprehensive training data. Moreover, due to the gradual nature of aging, similar-aged faces tend to share similarities despite their r...

Deep learning has enabled a straightforward, convenient method of road pavement infrastructure management that facilitates a secure, cost-effective, and efficient transportation network. Manual road pavement inspection is time-consuming and dangerous, making timely road repair difficult. This research showcases You Only Look Once version 5 (YOLOv5)...

As cyber threats evolve and grow progressively more sophisticated, cyber security is becoming a more significant concern in today's digital era. Traditional security measures tend to be insufficient to defend against these persistent and dynamic threats because they are mainly intuitional. One of the most promising ways to handle this ongoing probl...

This paper takes into account the aspect-based sentiment analysis of COVID-19 tweets, in order to understand human emotions and provide decision support to policymakers. People these days use social media to share thoughts and feelings in critical situations like COVID-19. After the World Health Organization (WHO) declared COVID-19 a pandemic, a si...

Cardiotocograms (CTGs) is a simple and inexpensive way for healthcare providers to monitor fetal health, allowing them to take step to lessen infant as well as mother died. The technology operates by emitting ultrasound pulses and monitoring the response, revealing information such as fetal heart rate (FHR), fetal movements, uterine contractions, a...

Spyware is a type of malware that is designed to infiltrate a device or steal personal information. Over the last decade, the number of people facing such dangers has risen from 12.4 million to 812.67 million. Since the spyware target platform has been enlarged, additional strategies using non-detectable approaches have been noticed. Traditional de...

In this fourth industrial revolution era, cyber-attacks are constantly increasing. A method called network traffic monitoring blueprint has been used to detect these unusual suspicious activities in the system. Fuzzers, Backdoors, DoS, Exploits, Reconnaissance, Shellcode, Worm, etc., are known as attacks that disrupt the functioning of a system. Th...

Covid text identification (CTI) is a crucial research concern in natural language processing (NLP). Social and electronic media are simultaneously adding a large volume of Covid-affiliated text on the World Wide Web due to the effortless access to the Internet, electronic gadgets and the Covid outbreak. Most of these texts are uninformative and con...

Due to the rising dependency on digital technology, cybersecurity has emerged as a more prominent field of research and application that typically focuses on securing devices, networks, systems, data and other resources from various cyber‐attacks, threats, risks, damages, or unauthorized access. Artificial intelligence (AI), also referred to as a c...

Due to the rising dependency on digital technology, cybersecurity has emerged as a more prominent field of research and application that typically focuses on securing devices, networks, systems, data and other resources from various cyber-attacks, threats, risks, damages, or unauthorized access. Artificial Intelligence (AI), also referred to as a c...

Good vaccine safety and reliability are essential for successfully countering infectious disease spread. A small but significant number of adverse reactions to COVID-19 vaccines have been reported. Here, we aim to identify possible common factors in such adverse reactions to enable strategies that reduce the incidence of such reactions by using pat...

Sentiment analysis has become crucial for the building of opinion mining systems due to the daily creation, sharing, and transfer of massive volumes of data and opinions via the Internet and other media. The sentiment analysis for movie recommendation is the main focus of this study. There are too many reviews and comments for movies to be manually...

p> Almost every web-based application is managed and operated through a number of websites, each of which is vulnerable to cyber-attacks that are mounted across the same networks used by the applications, with much less risk to the attacker than physical attacks. Such web-based attacks make use of a range of modern techniques-such as structured que...

Due to the digitization and Internet of Things revolutions, the present electronic world has a wealth of cybersecurity data. Efficiently resolving cyber anomalies and attacks is becoming a growing concern in today’s cyber security industry all over the world. Traditional security solutions are insufficient to address contemporary security issues du...

Since the advent of the worldwide COVID‐19 pandemic, analyzing public sentiment has become one of the major concerns for policy and decision‐makers. While the priority is to curb the spread of the virus, mass population (user) sentiment analysis is equally important. Though sentiment analysis using different state‐of‐the‐art technologies has been f...

Due to the digitization and Internet of Things revolutions, the present electronic world has a wealth of cybersecurity data. Efficiently resolving cyber anomalies and attacks is becoming a growing concern in today's cyber security industry all over the world. Traditional security solutions are insufficient to address contemporary security issues du...

K-means algorithm is one of the well-known unsupervised machine learning algorithms. The algorithm typically finds out distinct non-overlapping clusters in which each point is assigned to a group. The minimum squared distance technique distributes each point to the nearest clusters or subgroups. One of the K-means algorithm’s main concerns is to fi...

K-means algorithm is one of the well-known unsupervised machine learning algorithms. The algorithm typically finds out distinct non-overlapping clusters in which each point is assigned to a group. The minimum squared distance technique distributes each point to the nearest clusters or subgroups. One of the K-means algorithm's main concerns is to fi...

In recent times, due to the growing global population and increased food demand, smart agriculture is becoming more vital. In this context, Internet of Things (IoT) technologies have emerged as a significant pathway to innovative agricultural techniques. Due to their low capacity, these IoT nodes have faced energy limits and complicated routing met...

Online Social Networks (OSNs) have become inevitable for any new methodology both for viral promoting applications and instructing the creation of inciting information and data. As a result, finding influential users in OSNs is one of the most studied research problems. Existing research works paid less attention to the temporal factors associated...

Sentiment analysis is a process of extracting opinions into the positive, negative, or neutral categories from a pool of text using Natural Language Processing (NLP). In the recent era, our society is swiftly moving towards virtual platforms by joining virtual communities. Social media such as Facebook, Twitter, WhatsApp, etc are playing a very vit...

In this paper, we present a framework that automatically labels Latent Dirichlet Allocation (LDA) generated topics using sentiment and aspect terms from COVID-19 tweets to help the end-users by minimizing the cognitive overhead of identifying key topics labels. Social media platforms especially Twitter are considered as one of the most influential...

Cities are undergoing huge shifts in technology and operations in recent days, and ‘data science’ is driving the change in the current age of the Fourth Industrial Revolution (Industry 4.0 or 4IR). Extracting insights or actionable knowledge from city data and building a corresponding data-driven model is the key to making a city system automated a...

Substance abuse is the unrestrained and detrimental use of psychoactive chemical substances, unauthorized drugs, and alcohol that can ultimately lead a human to disastrous consequences. As patients with this behavior display a high value of relapse, the best intervention approach is to prevent it at the very beginning. In this paper, we propose a f...

In this paper, we mainly present a machine learning based approach to detect real-time phishing websites by taking into account URL and hyperlink based hybrid features to achieve high accuracy without relying on any third-party systems. In phishing, the attackers typically try to deceive internet users by masking a webpage as an official genuine we...

The Internet of Things (IoT) is one of the most widely used technologies today, and it has a significant effect on our lives in a variety of ways, including social, commercial, and economic aspects. In terms of automation, productivity, and comfort for consumers across a wide range of application areas, from education to smart cities, the present a...

In our civilizations, SMS continues to be an arguable communication tool despite the rattling development of protocol–predicated messaging approaches. Some businesses consider SMS as superior to e-mails for its representation. Spammers have been drawn to the pertinence of SMS for mobile phone freaks. The attacker can steal secret information by sen...

Due to the popularity of Internet of Things devices, the exponential progress of computer networks, and a plethora of associated applications, cybersecurity has recently attracted much attention in light of today's security problems. As a result, detecting various cyber‐attacks within a network and developing an effective cyber‐attacks prediction m...

COVID-19 cases are putting pressure on healthcare systems all around the world. Due to the lack of available testing kits, it is impractical for screening every patient with a respiratory ailment using traditional methods (RT-PCR). In addition, the tests have a high turn-around time and low sensitivity. Detecting suspected COVID-19 infections from...

Artificial intelligence (AI) is a leading technology of the current age of the Fourth Industrial Revolution (Industry 4.0 or 4IR), with the capability of incorporating human behavior and intelligence into machines or systems. Thus, AI-based modeling is the key to build automated, intelligent, and smart systems according to today’s needs. To solve r...

During the COVID-19 pandemic, many educational institutes switched from in-person to all virtual classes. Few educational institutes were well prepared for emergency remote teaching (ERT), whereas many others faced considerable problems in terms of preparation and delivery. As we know that remote teaching is highly dependent on technology infrastru...

Artificial intelligence (AI) is a leading technology of the current age of the Fourth Industrial Revolution (Industry 4.0 or 4IR), with the capability of incorporating human behavior and intelligence into machines or systems. Thus, AI-based modeling is the key to build automated, intelligent, and smart systems according to today’s needs. To solve r...

Cities are undergoing huge shifts in technology and operations in recent days, and `data science' is driving the change in the current age of the Fourth Industrial Revolution (Industry 4.0 or 4IR). Extracting insights or actionable knowledge from city data and building a corresponding data-driven model is the key to making a city system automated a...

The Internet of Things (IoT) is one of the most widely used technologies today, and it has a significant effect on our lives in a variety of ways, including social, commercial, and economic aspects. In terms of automation, productivity, and comfort for consumers across a wide range of application areas, from education to smart cities, the present a...

Smartphones are prone to SMS phishing due to the rapid growth in the availability of smart mobile technologies driven by Internet connections. Also, detecting phishing SMS is a challenging task due to the unstructured nature of SMS text data with non-linear complex correlations. In this concern, considering the recent advancements in the domain of...

Artificial Intelligence (AI) is a leading technology of the current age of the Fourth Industrial Revolution (Industry 4.0 or 4IR), with the capability of incorporating human behavior and intelligence into machines or systems. Thus AI-based modeling is the key to building automated, intelligent, and smart systems according to today's needs. To solve...

Ransomware is one of the most dangerous types of malware, which is frequently intended to spread through a network to damage the designated client by encrypting the client’s vulnerable data. Conventional signature-based ransomware detection technique falls behind because it can only detect known anomalies. When it comes to new and non-familiar rans...

Computer network attacks are evolving in parallel with the evolution of hardware and neural network architecture. Despite major advancements in Network Intrusion Detection System (NIDS) technology, most implementations still depend on signature-based intrusion detection systems, which can’t identify unknown attacks. Deep learning can help NIDS to d...

Emotion classification in text has growing interest among NLP experts due to the enormous availability of people’s emotions and its emergence on various Web 2.0 applications/services. Emotion classification in the Bengali texts is also gradually being considered as an important task for sports, e-commerce, entertainments, and security applications....

This book offers a clear understanding of the concept of context-aware machine learning including an automated rule-based framework within the broad area of data science and analytics, particularly, with the aim of data-driven intelligent decision making. Thus, we have bestowed a comprehensive study on this topic that explores multi-dimensional con...

In recent years, the ageing population is growing swiftly and ensuring proper healthcare for the elderly and physically challenged people has gained much attention from academic, medical or industrial experts. Many older people undergo sickness or inability, causing it challenging to look out of themselves concerning timely medicine taking. Any tri...

Point-of-interest (POI) recommendation system that tries to anticipate user’s next visiting location has attracted a plentiful research interest due to its ability in generating personalized suggestions. Since user’s historical check-ins are sequential in nature, Recurrent neural network (RNN) based models with context embedding shows promising res...

The COVID-19 outbreak has created effects on everyday life worldwide. Many research teams at major pharmaceutical companies and research institutes in various countries have been producing vaccines since the beginning of the outbreak. There is an impact of gender on vaccine responses, acceptance, and outcomes. Worldwide promotion of the COVID-19 va...

Computer network attacks are evolving in parallel with the evolution of hardware and neural network architecture. Despite major advancements in network intrusion detection system (NIDS) technology, most implementations still depend on signature-based intrusion detection systems, which cannot identify unknown attacks. Deep learning can help NIDS to...

In this paper, we present a framework that automatically labels latent Dirichlet allocation (LDA) generated topics using sentiment and aspect terms from COVID-19 tweets to help the end-users by minimizing the cognitive overhead of identifying key topics labels. Social media platforms, especially Twitter, are considered as one of the most influentia...

Smartphones are prone to SMS phishing due to the rapid growth in the availability of smart mobile technologies driven by Internet connections. Also, detecting phishing SMS is a challenging task due to the unstructured nature of SMS text data with non-linear complex correlations. In this concern, considering the recent advancements in the domain of...

Textual semantic similarity is a crucial constituent in many NLP tasks such as information retrieval, machine translation, information retrieval and textual forgery detection. It is a complicated task for rule-based techniques to address semantic similarity measures in low-resource languages due to the complex morphological structure and scarcity o...

Expert systems, a form of artificial intelligence (AI), are typically designed to solve many real-world problems by reasoning through knowledge, which is primarily represented as IF–THEN rules, with the information acquired from humans or domain experts. However, to assume such rules for personalized decision-making in an intelligent, context-aware...