Safety of AI Through the Lens of Security and Cryptography

Abstract:

AI techniques are being used in diverse domains where trustworthiness is a concern, including automotive systems, finance, healthcare, natural language processing, and malware detection. Of particular concern is the use of AI algorithms in cyber-physical systems (CPS), such as self-driving cars and aviation, where an adversary can cause serious consequences. Interest in this area of research has simply exploded. In this work, we will emphasize the need for a security and cryptography mindset in trustworthy machine learning, and then cover some lessons learned.

Speaker's Biography

Somesh Jha received his B.Tech from Indian Institute of Technology, New Delhi in Electrical Engineering. He received his Ph.D. in Computer Science from Carnegie Mellon University under the supervision of Prof. Edmund Clarke (a Turing award winner). Currently, Somesh Jha is the Lubar Professor in the Computer Sciences Department at the University of Wisconsin (Madison). His work focuses on analysis of security protocols, survivability analysis, intrusion detection, formal methods for security, and analyzing malicious code. Recently, he has focused on trustworthy ML. Somesh Jha has published several articles in highly-referenced conferences and prominent journals. He has won numerous best-paper and distinguished-paper awards. Prof. Jha received the CAV award for his work on CEGAR, and also has received the IIT-Delhi Distinguished Alumni award. Prof. Jha is a fellow of the ACM, IEEE, and AAAS.