Non-Deterministic Planning for Hyperproperty Verification
This work addresses the verification of complex security properties for systems with uncertain actions, though it appears incremental as it builds on existing logics and planning frameworks.
The paper tackles the problem of automated verification of hyperproperties, which relate multiple system paths for security and information-flow policies, by showing that non-deterministic planning can serve as an intermediate language, with a prototype tool yielding encouraging experimental results.
Non-deterministic planning aims to find a policy that achieves a given objective in an environment where actions have uncertain effects, and the agent - potentially - only observes parts of the current state. Hyperproperties are properties that relate multiple paths of a system and can, e.g., capture security and information-flow policies. Popular logics for expressing temporal hyperproperties - such as HyperLTL - extend LTL by offering selective quantification over executions of a system. In this paper, we show that planning offers a powerful intermediate language for the automated verification of hyperproperties. Concretely, we present an algorithm that, given a HyperLTL verification problem, constructs a non-deterministic multi-agent planning instance (in the form of a QDec-POMDP) that, when admitting a plan, implies the satisfaction of the verification problem. We show that for large fragments of HyperLTL, the resulting planning instance corresponds to a classical, FOND, or POND planning problem. We implement our encoding in a prototype verification tool and report on encouraging experimental results.