I am a cyber security professional and computer scientist with broadly interests in practical aspects of problems arising in critical infrastructure protection, including but not limited to intrusion detection, machine learning and AI. On a low resolution, my research lies primarily in the union of machine learning, and theoretical cyber security, using tools from Artificial Intelligence, trust management, and statistical methods. Most recently, my research focuses on the context-aware zero-trust method, with emphasis on IoT-based trust management and security guarantees for self-driving vehicles security. Overall, I work in the gap between cyber security and machine learning analysis and I thrive to bridge gaps between these highly related but nevertheless at times independent fields. 

My research interests in Computer Science domain encompass a wide spectrum, with a primary focus on intelligent intrusion and anomaly detection methods,

Machine learning, and cyber security. 

Feel free to contact me at [ izhar@nuaa.edu.cn ] to explore exciting research opportunities together.  I am actively seeking undergraduate and master's students

 to join our team for hands-on research to expand your knowledge and make a meaningful impact on the real world.