AI Based behavior Analysis for Cyber Security Enhancing Cyber Resilience through AI-Driven Behavioral Analysis:  A Proactive Framework for Anomaly Detection

S. Jayakrishnan; A. Jesudasan; Dr. A. S. Arunachalam

doi:https://www.doi.org/10.59256/indjcst.20260502012

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AI Based behavior Analysis for Cyber Security Enhancing Cyber Resilience through AI-Driven Behavioral Analysis: A Proactive Framework for Anomaly Detection

S. Jayakrishnan1A. Jesudasan2Dr. A. S. Arunachalam3

¹ ² Research Scholar, Department of computer science, Vels Institute of Science Technology and Advanced Studies (VISTAS), Chennai, Tamilnadu, India. ³ Research Supervisor, Department of Computer Science & IT Vels Institute of Science Technology and Advanced Studies (VISTAS). Chennai, Tamilnadu, India.

Published Online: May-August 2026

Pages: 120-122

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↗ https://www.doi.org/10.59256/indjcst.20260502012

Abstract

Traditional cybersecurity paradigms, primarily dependent on static signature-based detection, are increasingly inadequate against the evolution of polymorphic malware, zero-day exploits, and sophisticated insider threats. This paper proposes a robust framework for AI-based Behavioral Analysis that transitions defense mechanisms from reactive to predictive. By leveraging Machine Learning (ML) and Deep Learning (DL) architectures—specifically long Short-Term Memory (LSTM) networks and Isolation Forests—the proposed system ingests multi-source telemetry from network traffic and user endpoints to establish dynamic "normalcy" baselines.

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AI Based behavior Analysis for Cyber Security Enhancing Cyber Resilience through AI-Driven Behavioral Analysis: A Proactive Framework for Anomaly Detection

Published Online: May-August 2026

Pages: 120-122

Cite this article

Abstract

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