Untangle: A Principled Framework to Design Low-Leakage, High-Performance Dynamic Partitioning Schemes

Abstract

Partitioning a hardware structure dynamically among multiple security domains leaks some information but can deliver high performance. To understand the performance-security tradeoff of dynamic partitioning, it would be useful to formally quantify the leakage of these schemes. Unfortunately, this is hard, as what partition resizing decisions are made and when they are made are entangled. In this paper, we present Untangle, a novel framework for constructing low-leakage and high-performance dynamic partitioning schemes. Untangle formally splits the leakage into leakage from deciding what resizing action to perform (action leakage) and leakage from deciding when the resizing action occurs (scheduling leakage). Based on this breakdown, Untangle introduces a set of principles that decouple program timing from the action leakage. Moreover, Untangle introduces a new way to model the scheduling leakage without analyzing program timing. With these techniques, Untangle quantifies the leakage in a dynamic resizing scheme more tightly than prior work. To demonstrate Untangle, we apply it to dynamically partition the last-level cache. On average, workloads leak 78% less under Untangle than under a conventional dynamic partitioning approach, for the same workload performance.