Helium: Quantifying Microarchitectural Side-Channel Leakage with Probabilistic Guarantees

Constant-time programming ensures zero leakage of program secrets via hardware side channels by preventing secrets from being passed to unsafe instructions. However, as microarchitectures employ more data-dependent optimizations to boost performance, more instructions become unsafe, and constant-time code incurs high performance cost. A promising alternative is bounding leakage according to application-specific requirements, but principled methods for doing so remain elusive. We present Helium, a three-part framework for quantifying hardware side-channel leakage of program secrets on specific microarchitectures. First, it leverages a new metric for expressing probabilistic privacy guarantees. Second, it employs a novel formalism for encoding how arbitrary hardware side channels give rise to attacker observations. Third, it provides two analysis techniques-symbolic (precise) and simulation (conservatively approximate)-to determine whether high-leakage observations occur with sufficiently low probability for a given victim program, secret input, microarchitecture, and attacker model. Through four case studies spanning cryptographic and image processing applications, Helium demonstrates the necessity of considering both program and microarchitecture when assessing security-performance trade-offs. In one case, improved performance does not imply worse security; in another, accepting small leakage risk enables significant performance overhead reduction compared to a recent zero-leakage software side-channel defense.