In this paper, we describe and analyze an island-based random dynamic voltage scaling (iRDVS) approach to thwart power side-channel attacks. We first analyze the impact of the number of independent voltage islands on the resulting signal-to-noise ratio and trace misalignment. As part of our analysis of misalignment, we propose a novel unsupervised machine learning (ML) based attack that is effective on systems with three or fewer independent voltages. Our results show that iRDVS with four voltage islands, however, cannot be broken with 200k encryption traces, suggesting that iRDVS can be effective. We finish the talk by describing an iRDVS test chip in a 12nm FinFet process that incorporates three variants of an AES-256 accelerator, all originating from the same RTL. This included a synchronous core, an asynchronous core with no protection, and a core employing the iRDVS technique using asynchronous logic. Lab measurements from the chips indicated that both unprotected variants failed the test vector leakage assessment (TVLA) security metric test, while the iRDVS was proven secure in a variety of configurations.

This paper proposes the method of generating asynchronous circuits from hardware description language specifications by clustering the synthesized gates into asynchronous pipeline stages while preserving liveness, meeting throughput and latency constraints, and minimizing area. This method provides a form of automatic pipelining in which the throughput of the overall design is not limited to the clock frequency or the level of pipelining in the original Register-Transfer Level (RTL) specification. The method is design-style agnostic and is thus applicable to many asynchronous design styles.