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

#cyber-attack #anomaly-detection #mitigation #machine-learning #deep-learning #privacy #security
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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 mechanisms.


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  • 40 Gould St.
  • Toronto, Ontario
  • Canada M5B 2K3
  • Building: Kerr Hall South
  • Room Number: KHS134
  • Contact Event Host
  • Starts 03 October 2025 04:00 AM UTC
  • Ends 30 October 2025 04:00 AM UTC
  • No Admission Charge

  Speakers

Sajal of University of Northern British Columbia

Topic:

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 mechanisms.

Biography:

Dr. Sajal Saha (Senior Member, IEEE) is an Assistant Professor of Computer Science at the University of Northern British Columbia (UNBC), Canada, and Founder of the INFORM Lab. He received the Ph.D. degree in Computer Science from Western University, Canada, where he was nominated for the Governor General’s Gold Medal, and the M.Sc. degree in Computer Science from Brock University, Canada, where he was recognized as a Distinguished Graduate. His research focuses on Internet traffic analysis, cyber-attack detection and mitigation, privacy-preserving and federated learning, and quantum-secure AI systems. Dr. Saha has authored numerous peer-reviewed publications, and his work has been supported through national and institutional research grants. He also serves as a reviewer and technical program committee member for international journals and conferences.

 

Email:

Address:3333 University Way, , Prince George, British Columbia, Canada, V2N 4Z9

Sajal