Architectural Mimicry: Innovative Instructions to Efficiently Address Control-Flow Leakage in Data-Oblivious Programs

Abstract

The control flow of a program can often be observed through side-channel attacks. Hence, when control flow depends on secrets, attackers can learn information about these secrets. Widely used software-based countermeasures ensure that attacker-observable aspects of the control flow do not depend on secrets, relying on techniques like dummy execution (for balancing code) or conditional execution (for linearizing code). In the current state-of-practice, the primitives to implement these techniques have to be found in an existing instruction set architecture (ISA) that was not designed a priori to provide them, leading to performance, security, and portability issues. To counter these issues, this paper proposes lightweight hardware extensions for supporting these techniques in a principled way. We propose (1) a novel hardware mechanism (mimic execution), that executes an instruction stream only for its attacker-observable effects, and suppresses (most) architectural effects, and (2) ISA support (called AMi, for