This monograph examines how AI, machine learning, deep learning, and intelligent analytics support threat detection, attack prediction, security monitoring, vulnerability assessment, and automated incident response.
Abstract
Artificial Intelligence and Cybersecurity: Innovations, Challenges, and Applications explores the transformative role of artificial intelligence in modern cybersecurity. The monograph examines how AI, machine learning, deep learning, and intelligent analytics support threat detection, attack prediction, security monitoring, vulnerability assessment, and automated incident response. It addresses emerging cyber threats, AI-enabled attacks, adversarial machine learning, intelligent defense mechanisms, blockchain security, autonomous systems, and next-generation network protection. The book also discusses challenges related to privacy, trust, explainability, scalability, and ethical AI deployment. It provides researchers, academicians, students, and cybersecurity professionals with contemporary knowledge and practical perspectives on building intelligent and resilient digital security systems.
Cybersecurity Transformation: Artificial Intelligence, Cloud, Data, and Digital Resilience examines the transformation of modern cybersecurity through artificial intelligence, cloud computing, data-driven security, and resilient digital architectures. The monograph explores intelligent threat detection, machine learnin...
The findings indicate that AI can improve the speed, scalability, adaptability, and proactive capabilities of cybersecurity systems, however, challenges including data quality, false positives and negatives, adversarial attacks, privacy risks, lack of explainability, computational requirements, and ethical concerns rem...
Gurwinder Singh· International Journal of Sci...· 0 citations
The review finds that artificial intelligence enables proactive threat detection, anomaly identification, and the automation of analysis and response at a scale beyond human capacity, yet its effectiveness is constrained by adversarial machine learning, data quality and drift, false positives, opacity, and the dual use...
N. Hussain· WORLD JOURNAL OF INNOVATION...· 0 citations
Artificial intelligence (AI) has emerged as a transformative force in cybersecurity, offering capabilities that extend far beyond the static, rule-based defenses of the past. Machine learning, deep learning, and natural language processing techniques are increasingly embedded in intrusion detection systems, threat inte...
Nicolas Guzman Camacho· Journal of Artificial Intell...· 0 citations
This paper argues that the convergence of AI and cybercrime requires a recalibration of international and domestic cybersecurity law, including clearer liability standards for AI-enabled offences, updated treaty frameworks, and the development of a risk-based, technology-neutral cybersecurity architecture capable of ad...
Basabi Pandey, Mansi Srivastava, Seema Choudhary et al.· International Journal for Re...· 0 citations
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