Efficient monitoring of hyperproperties using prefix trees

Hyperproperties, such as non-interference and observational determinism, relate multiple computation traces with each other and are thus not monitorable by tools that consider computations in isolation. We present the monitoring approach implemented in the latest version of $$\text {RVHyper}$$ , a runtime verification tool for hyperproperties. The input to the tool are specifications given in the temporal logic $$\text {HyperLTL}$$ , which extends linear-time temporal logic (LTL) with trace quantifiers and trace variables. $$\text {RVHyper}$$ processes execution traces sequentially until a violation of the specification is detected. In this case, a counterexample, in the form of a set of traces, is returned. $$\text {RVHyper}$$ employs a range of optimizations: a preprocessing analysis of the specification and a procedure that minimizes the traces that need to be stored during the monitoring process. In this article, we introduce a novel trace storage technique that arranges the traces in a tree-like structure to exploit partially equal traces. We evaluate $$\text {RVHyper}$$ on existing benchmarks on secure information flow control, error correcting codes, and symmetry in hardware designs. As an example application outside of security, we show how $$\text {RVHyper}$$ can be used to detect spurious dependencies in hardware designs.