Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Faculty Publications Book Chapter Faculty Publications- Book Chapter Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Creator An entity primarily responsible for making the resource Deepti, A.R.; Manimekala, B.; Basith, Farzeen; Selvaraj, Vibinchandar Title A name given to the resource Behavioral analysis of malicious activities in AI comprehensive analysis Date A point or period of time associated with an event in the lifecycle of the resource 01-01-2025 Source A related resource from which the described resource is derived Improving Threat Detection, Network Security, and Incident Response With AI;pp.83-112 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.4018/979-8-3373-2115-8.ch004" target="_blank" rel="noreferrer noopener">https://doi.org/10.4018/979-8-3373-2115-8.ch004</a> <br /><br /><a href="https://www.scopus.com/pages/publications/105013254773?origin=resultslist" target="_blank" rel="noreferrer noopener">https://www.scopus.com/pages/publications/105013254773?origin=resultslist</a> Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant 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 Description An account of the resource 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. Publisher An entity responsible for making the resource available IGI Global Relation A related resource ISBN: 979-833732117-2; 979-833732115-8; Language A language of the resource English Type The nature or genre of the resource Book chapter Rights Information about rights held in and over the resource Restricted Access; Hardcopy may be available in the library Format The file format, physical medium, or dimensions of the resource online