Projects

Innovative Autonomous Risk Detection and Mitigation Powered by Collaborative Machine Learning for Zero-trust Systems

• IoT anomaly detection powered by ML models. 
• Investigation of AI powered attacks on IoT and countermeasures. 

The project aims to develop a framework, based on a sound theoretical foundation, for automated detection and mitigation of cyber risks to improve the security of computer systems in zero-trust environments. Specifically, this project introduces a novel framework that uses state-of-the-art collaborative machine learning techniques to develop a suite of adaptive solutions capable of detecting, responding, and mitigating various cyber-attacks on networked systems.

• AMD Ryzen Threadripper 4 GPU AI Deep Learning Workstation PC

• Development of fast and real-time intrusion/anomaly detection scheme

• Lightweight machine learning algorithms for IoT applications

• Autonomous risk response scheme