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Original Article

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

S. Jayakrishnan1 A. Jesudasan2 Dr. 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

References

1. System Design: CrowdStrike (2023). "AI-Powered Behavioral Analysis in Cybersecurity." CrowdStrike Resource.
2. Threat Detection: Sarker, I. H. (2024). "Advancing cybersecurity: a comprehensive review of AI-driven detection techniques."
SpringerLink.
3. Transparency: ScienceDirect (2024). "Explainable AI for cybersecurity automation, intelligence and trustworthiness." ScienceDirect.
4. Complexity: Springer (2024). "Advancing cybersecurity: a comprehensive review of AI- driven detection techniques." Source.
5. Privacy: IEEE Xplore (2023). "Federated Learning for Cyber Security: Concepts, Challenges, and Future Directions."
6. Accuracy: Sarker, I. H. (2024). "Examining the Impact of User Behavior Analysis on Threat Detection." Source.
7. Adversarial Risks: ScienceDirect (2024). "Explainable AI for cybersecurity automation, intelligence and trustworthiness." Source.
https://www.ijcrt.org/papers/IJCRT2410110.pdf, https://link.springer.com/article/10.1186/s40537-024-00957-y

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