Theme 4: Security, Privacy, and Correctness

The move toward an ecosystem rich in accelerators processing sensitive data calls for a rethink of security and correctness mechanisms. While the large majority of current security frameworks tie security properties to users, applications, or hardware/software systems, we need paradigms that are more data centric. Further, we will design new Trusted Execution Environments (TEEs) for accelerators. These will be  customized to the target accelerator,  evolvable to adapt to  changes in the environment, and, importantly, automatically generated by a compiler. We also propose comprehensive and principled verification approaches for security and privacy assurance of accelerators—such as RTL-level analysis to discover security vulnerabilities. Finally, as accelerators aim for short design-to-deployment timelines, we  will develop new techniques for their quick and thorough correctness verification.

A framework for RL-based fuzzing and RTL introspection for security verification of complex security properties.
A framework for RL-based fuzzing and RTL introspection for verification of complex security properties (Courtesy of Radu Teodorescu).

Papers and Presentations: