CSNet 2024 Keynotes 

Keynote #1

Title:  Generative AI and Large Language Models for Cyber Security: All Insights You Need

Abstract: This keynote will explore the transformative potential of Generative AI and Large Language Models (LLMs) in cybersecurity, drawing from a comprehensive review of their applications in hardware design security, intrusion detection, software engineering, design verification, cyber threat intelligence, malware detection, and phishing detection. We will highlight the evolution and advancements of models such as GPT-4, GPT-3.5, Mixtral-8x7B, BERT, Falcon2, and LLaMA, alongside an analysis of LLM vulnerabilities and mitigation strategies. Evaluating 42 LLM models in cybersecurity knowledge and hardware security, we will identify their strengths and weaknesses, assess cybersecurity datasets, and explore advanced strategies like Half-Quadratic Quantization (HQQ), Reinforcement Learning with Human Feedback (RLHF), Direct Preference Optimization (DPO), Quantized Low-Rank Adapters (QLoRA), and Retrieval-Augmented Generation (RAG). This talk aims to provide a strategic direction for integrating LLMs into future cybersecurity frameworks, emphasizing innovation and robust model deployment to safeguard against evolving threats.

Bio: Mohamed Amine Ferrag earned his Bachelor’s, Master’s, Ph.D., and Habilitation degrees in Computer Science from Badji Mokhtar Annaba University, Algeria, completing his studies in 2008, 2010, 2014, and 2019, respectively. He served as an Associate Professor in the Department of Computer Science at Guelma University, Algeria, from 2014 until 2022. Concurrently, from 2019 to 2022, he held the position of Senior Researcher at the NAU-Lincoln Joint Research Center of Intelligent Engineering, based at Nanjing Agricultural University in China. As of 2022, Dr. Ferrag is Lead Researcher at the Artificial Intelligence & Digital Science Research Center at the Technology Innovation Institute in Abu Dhabi, United Arab Emirates. Dr. Ferrag’s research is primarily focused on a spectrum of topics within the cybersecurity domain, including wireless network security, network coding security, applied cryptography, blockchain technology, generative AI, software security, and the application of AI in cybersecurity. His scholarly output includes over 150 papers published in international journals and conference proceedings. He has consistently been named on Stanford University’s list of the world’s top 2% of scientists four times from 2020 through 2023. Dr. Ferrag also contributes to the academic community as an associate editor for prestigious journals, such as the IEEE Internet of Things Journal. He has more than 9000 citations and an h-index of 39 (https://scholar.google.fr/citations?user=IkPeqxMAAAAJ&hl=fr ).