Mapping Synthesis for Hyperproperties

• Published in: 2022 IEEE 35th Computer Security Foundations Symposium (CSF) pp. 486 - 500
• Main Authors: Hsu, Tzu-Han, Bonakdarpour, Borzoo, Kang, Eunsuk, Tripakis, Stavros
• Format: Conference Proceeding
• Language: English
• Published: IEEE 01.08.2022
• Subjects: Games; Hardware; Hyperproperties; Information-flow security; Model checking; Passwords; Refinement; Synthesis; System analysis and design
• DOI: 10.1109/CSF54842.2022.9919679

In system design, high-level system models typically need to be mapped to an execution platform (e.g., hardware, environment, compiler, etc). The platform may naturally strengthen some constraints or weaken some others, but it is expected that the low-level implementation on the platform should preserve all the functional and extra-functional properties of the model, including the ones for information-flow security. It is, however, well known that simple notions of refinement do not preserve information-flow security properties. In this paper, we propose a novel automated mapping synthesis approach that preserves hyperproperties expressed in the temporal logic HyperLTL. The significance of our technique is that it can handle formulas with quantifier alternations, which is typically the source of difficulty in refinement for information-flow security policies. We reduce the mapping synthesis problem to HyperLTL model checking and leverage recent efforts in bounded model checking for hyperproperties. We demonstrate how mapping synthesis can be used in various applications, including enforcing non-interference and automating secrecy-preserving refinement mapping. We also evaluate our approach using the battleship game and password validation use cases.