Keynote Talk
Machine Learning for Hardware Security – from Application to Transformative Impact
Department of Electrical and Computer Engineering
University of Illinois Chicago, USA
Abstract: With a broad spectrum of modern hardware security attacks, integrated circuit (IC) trust has become a primary concern across levels of design abstraction and fabrication. Cutting edge benefits of ML enable opportunities for ML-guided, secure electronic design and manufacturing. However, the complexity and variety of ML models, algorithms, and architectures pose a significant challenge — application of ML without advance ML expertise is at best sub-optimal. In addition, in-depth insight into modern complex circuits, design and fabrication processes, and hardware security threats is required to develop resilient ICs. How to create a transformative impact in hardware security with ML is still an open question.
This talk will provide an overview of various security vulnerabilities as well as related design challenges, needs, and learning-guided trust methods. We will discuss recent ML-based approaches for on-chip detection of side-channel attacks and emerging directions for trusted fabrication in untrusted foundries, considering threats such as reverse engineering, overbuilding, counterfeiting, and IP piracy. We will then use a framework for hardware Trojan detection as a demonstration vehicle for closing the expertise gap among IC design, cybersecurity, and ML researchers as part of a transformative ML hardware security effort. The talk will conclude with a perspective on future opportunities at the intersection of these fields.
Biography: Inna Partin-Vaisband received her B.Sc. in computer engineering and M.Sc. in electrical engineering from the Technion-Israel Institute of Technology, Haifa, Israel, in, respectively, 2006 and 2009, and the Ph.D. in electrical engineering from the University of Rochester, Rochester, NY in 2015. She is currently with the Department of Electrical and Computer Engineering at the University of Illinois Chicago, where she is an Assistant Professor and the Director of High-Performance Circuits and Systems Laboratory. Between 2003 and 2009, she held a variety of software and hardware research and development positions at Tower Semiconductor, G-Connect, and IBM, all in Israel.
Her primary research and teaching interests include high-performance digital and mixed-signal ICs and VLSI system design. Her current research focused on innovation in the areas of hardware security, ML-guided design automation, and AI hardware. Special emphasis has been placed on distributed power delivery and locally intelligent power management, which is described in her book, On-Chip Power Delivery and Management, 4th Edition. Dr. Partin-Vaisband is one of the seven worldwide recipients of the 2022 Google Research Scholar Award in Systems category. She was the Guest Editor of the IEEE Journal on Emerging and Selected Topics in Circuits and Systems and Associate Guest Editor of the IEEE Journal on Emerging and Selected Topics in Power Electronics. She is an Associate Editor of the Microelectronics Journal and has served on the Technical Program and Organization Committees of various conferences.
