Harnessing Artificial Intelligence in Cybersecurity: An Intelligent Vulnerability Assessment Approach for 5G Edge Networks
5G technology will play a crucial role in global economic growth through numerous industrial developments. However, while it is essential to ensure the security of these developed systems, 5G brings unique security challenges. Research led by SUNY Poly Assistant Professor Hisham Kholidy aims to contribute explicitly to the need for effective artificial intelligence-based approaches to identify and assess the vulnerabilities in 5G networks in an accurate, salable, and dynamic way.
The proposed approaches develop an optimized mechanism based on the Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS), Intelligent Multi-Criteria Decision Making (MCDM) methods, Competitive Markov Model, and hexagonal fuzzy numbers to analyze the vulnerabilities in 5G Edge networks from the attacker perspective while considering the dynamic and scalable Edge properties.
This research is taking place at SUNY Poly’s Advanced Cybersecurity Research Laboratory (ACRL Lab) where Dr. Kholidy and his team are developing a cybersecurity testbed for the 5G networks to test and evaluate the proposed approaches, in collaboration with the Air Force Research Laboratory-Information DIrectorate (AFRL/RI) in Rome, NY.