AI-Driven Cybersecurity and Threat Intelligence
Cyber Automation, Intelligent Decision-Making and Explainability
Chapter
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...
Chapter
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...
Book
Cyber Automation, Intelligent Decision-Making and Explainability
Chapter
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 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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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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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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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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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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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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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...
Chapter and Conference Paper
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...
Chapter and Conference Paper
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 ...
Chapter and Conference Paper
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 signa...
Chapter
In the previous chapter, we have presented an approach for discovering behavioral rules of individual mobile phone users based on multi-dimensional contexts (temporal, spatial, and social context) utilizing th...
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Deep learning is considered as a part of the broader family of machine learning methods, which is based on artificial neural networks with representation learning. In the earlier chapters, we have presented me...
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Context-aware machine learning typically focuses on applications that learn from contextual data and develop their decision-making abilities over time. To make intelligent decisions in different context-aware ...
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An expert system is a computer system that simulates the decision-making abilities of a human expert in artificial intelligence (AI). Expert systems, rather than using traditional procedural code, are structur...
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Context-awareness has recently received much attention in academia and industry for a variety of applications. Due to its intelligence in technologies and availability in various real-world applications, there...
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The concept of context-aware computing has grown in popularity in recent years, especially with the current evolution of smart mobile devices. Recent advancements in smartphones and their sensing capabilities ...