48 Result(s)
within
Chapter
Iqbal H. Sarker
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Chapter
AI-Enabled Cybersecurity for IoT and Smart City Applications
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 networ...
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Chapter
AI for Critical Infrastructure Protection and Resilience
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, whi...
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Cybersecurity Background Knowledge: Terminologies, Attack Frameworks, and Security Life Cycle
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. ...
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Detecting Anomalies and Multi-attacks Through Cyber Learning: An Experimental Analysis
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 b...
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Cybersecurity Data Science: Toward Advanced Analytics, Knowledge, and Rule Discovery for Explainable AI Modeling
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 i...
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AI for Enhancing ICS/OT Cybersecurity
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 ar...
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Chapter and Conference Paper
Data-Driven Intelligence Can Revolutionize Today’s Cybersecurity World: A Position Paper
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 ...
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CyberAI: A Comprehensive Summary of AI Variants, Explainable and Responsible AI for Cybersecurity
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 we...
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Introduction to AI-Driven Cybersecurity and Threat Intelligence
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 cyber...
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Learning Technologies: Toward Machine Learning and Deep Learning for Cybersecurity
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...
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Chapter
Generative AI and Large Language Modeling in Cybersecurity
Cybersecurity is encountering new challenges demanding innovative solutions due to the complexity and frequency of cyberattacks progressing. Artificial intelligence (AI), particularly generative AI, has emerge...
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Chapter and Conference Paper
A Stacked Ensemble Spyware Detection Model Using Hyper-Parameter Tuned Tree Based Classifiers
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....
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Chapter and Conference Paper
Diagnosis and Classification of Fetal Health Based on CTG Data Using Machine Learning Techniques
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 ...
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Chapter and Conference Paper
Classifying Sentiments from Movie Reviews Using Deep Neural Networks
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 s...
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Chapter and Conference Paper
Cyber-Attack Detection Through Ensemble-Based Machine Learning Classifier
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...
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Chapter and Conference Paper
Aspect Based Sentiment Analysis of COVID-19 Tweets Using Blending Ensemble of Deep Learning Models
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 shar...
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Chapter and Conference Paper
Detecting Smishing Attacks Using Feature Extraction and Classification Techniques
Phishing scams via SMS have become a common phenomenon due to the widespread use of smartphones and the availability of mobile Internet technologies. Identifying a phishing SMS via analyzing unstructured short...
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Chapter and Conference Paper
Automatic Malware Categorization Based on K-Means Clustering Technique
The android operating system is a popular operating system for mobile phone applications. This is also known as an open-source operating system so that the developers can easily update and add new features to ...
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Chapter and Conference Paper
Genetic Algorithm-Based Optimal Deep Neural Network for Detecting Network Intrusions
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 implem...
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Chapter and Conference Paper
SATLabel: A Framework for Sentiment and Aspect Terms Based Automatic Topic Labelling
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 ...
