Towards Next-Generation Cyber Defense: Detection and Mitigation with Machine Learning, Deep Learning, and LLMs

Cyber-attacks continue to evolve in scale and sophistication, posing significant challenges to the security of modern networked systems. This talk will present a review of recent advances in cyber-attack detection using machine learning and deep learning, highlighting both their strengths and limitations. I will discuss my recent research contributions on integrating forecasting, anomaly detection, explainable AI, and large language models (LLMs) to build intelligent and autonomous mitigation strategies. The talk will conclude with future research directions for next-generation cyber defense, emphasizing the role of explainability, privacy-preserving methods, and adaptive response <a href="http://mechanisms.

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Speaker(s): Sajal, Sajal

Room: KHS134, Bldg: Kerr Hall South, 40 Gould St., Toronto, Ontario, Canada, M5B 2K3, Virtual: https://events.vtools.ieee.org/m/504815