Behavioral analysis of malicious activities in AI comprehensive analysis
The chapter provides a detailed overview of behavioral analysis evolved in AI security systems, from rule- based methods to advanced AI- driven approaches with verified threat prediction accuracy. Finance, healthcare, and telecommunications sectors show empirical evidence of modern systems by processing huge data volumes with exceptional threat detection capabilities. Research from Microsoft, IBM, and Google confirms AI- enabled security significantly reduces the time of threat identification compared to traditional approaches. The technical analysis reveals cloud-n ative solutions offer greater cost- efficiency and performance than on-premise alternatives, with measurable ROI improvements. The study examines behavioral analysis integration with machine learning, advanced persistent threat detection challenges, implementation strategies across different organizational contexts, and ethical considerations essential for developing effective security systems. 2026, IGI Global Scientific Publishing. All rights reserved.
Deepti, A.R.; Manimekala, B.; Basith, Farzeen; Selvaraj, Vibinchandar
Improving Threat Detection, Network Security, and Incident Response With AI;pp.83-112
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https://doi.org/10.4018/979-8-3373-2115-8.ch004 https://www.scopus.com/pages/publications/105013254773?origin=resultslist
Deepti A.R., Acharya Institute of Graduate Studies, India; Manimekala B., Christ University, India; Basith F., Acharya Institute of Graduate Studies, India; Selvaraj V., Acharya Institute of Graduate Studies, India