Advancing Cyber Defense Systems through Machine Learning, Deep Learning, and Large Language Models

#AI #deep-learning #cyber-attack #machine-learning
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As cyber-attacks grow increasingly sophisticated and large-scale, they present escalating challenges to the security of modern networked systems. This presentation reviews recent advances in cyber-attack detection through machine learning and deep learning, examining their capabilities as well as their current limitations. I will share my recent research on integrating forecasting, anomaly detection, explainable AI, and large language models (LLMs) to develop intelligent and autonomous mitigation frameworks. The talk will conclude by outlining future directions for next-generation cyber defense, with a focus on explainability, privacy-preserving techniques, and adaptive response mechanisms.



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  • 3333 University Way
  • Prince George, British Columbia
  • Canada V2N 4Z9
  • Building: Building 10
  • Room Number: 4520

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  Speakers

Sajal Saha of Department of Computer Science, University of Northern British Columbia

Topic:

Advancing Cyber Defense Systems through Machine Learning, Deep Learning, and Large Language Models

As cyber-attacks grow increasingly sophisticated and large-scale, they present escalating challenges to the security of modern networked systems. This presentation reviews recent advances in cyber-attack detection through machine learning and deep learning, examining their capabilities as well as their current limitations. I will share my recent research on integrating forecasting, anomaly detection, explainable AI, and large language models (LLMs) to develop intelligent and autonomous mitigation frameworks. The talk will conclude by outlining future directions for next-generation cyber defense, with a focus on explainability, privacy-preserving techniques, 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.