452 research outputs found

    Quantitative Information Flow as Safety and Liveness Hyperproperties

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    We employ Clarkson and Schneider's "hyperproperties" to classify various verification problems of quantitative information flow. The results of this paper unify and extend the previous results on the hardness of checking and inferring quantitative information flow. In particular, we identify a subclass of liveness hyperproperties, which we call "k-observable hyperproperties", that can be checked relative to a reachability oracle via self composition.Comment: In Proceedings QAPL 2012, arXiv:1207.055

    A Temporal Logic for Hyperproperties

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    Hyperproperties, as introduced by Clarkson and Schneider, characterize the correctness of a computer program as a condition on its set of computation paths. Standard temporal logics can only refer to a single path at a time, and therefore cannot express many hyperproperties of interest, including noninterference and other important properties in security and coding theory. In this paper, we investigate an extension of temporal logic with explicit path variables. We show that the quantification over paths naturally subsumes other extensions of temporal logic with operators for information flow and knowledge. The model checking problem for temporal logic with path quantification is decidable. For alternation depth 1, the complexity is PSPACE in the length of the formula and NLOGSPACE in the size of the system, as for linear-time temporal logic

    Robust Hyperproperty Preservation for Secure Compilation (Extended Abstract)

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    We map the space of soundness criteria for secure compilation based on the preservation of hyperproperties in arbitrary adversarial contexts, which we call robust hyperproperty preservation. For this, we study the preservation of several classes of hyperproperties and for each class we propose an equivalent "property-free" characterization of secure compilation that is generally better tailored for proofs. Even the strongest of our soundness criteria, the robust preservation of all hyperproperties, seems achievable for simple transformations and provable using context back-translation techniques previously developed for showing fully abstract compilation. While proving the robust preservation of hyperproperties that are not safety requires such powerful context back-translation techniques, for preserving safety hyperproperties robustly, translating each finite trace prefix back to a source context seems to suffice.Comment: PriSC'18 final versio

    Emergent Behavior in Cybersecurity

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    We argue that emergent behavior is inherent to cybersecurity.Comment: 2 pages, HotSoS'2014 (2014 Symposium and Bootcamp on the Science of Security

    Deductive Controller Synthesis for Probabilistic Hyperproperties

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    Probabilistic hyperproperties specify quantitative relations between the probabilities of reaching different target sets of states from different initial sets of states. This class of behavioral properties is suitable for capturing important security, privacy, and system-level requirements. We propose a new approach to solve the controller synthesis problem for Markov decision processes (MDPs) and probabilistic hyperproperties. Our specification language builds on top of the logic HyperPCTL and enhances it with structural constraints over the synthesized controllers. Our approach starts from a family of controllers represented symbolically and defined over the same copy of an MDP. We then introduce an abstraction refinement strategy that can relate multiple computation trees and that we employ to prune the search space deductively. The experimental evaluation demonstrates that the proposed approach considerably outperforms HyperProb, a state-of-the-art SMT-based model checking tool for HyperPCTL. Moreover, our approach is the first one that is able to effectively combine probabilistic hyperproperties with additional intra-controller constraints (e.g. partial observability) as well as inter-controller constraints (e.g. agreements on a common action)

    Robust Hyperproperty Preservation for Secure Compilation (Extended Abstract)

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    We map the space of soundness criteria for secure compilation based on the preservation of hyperproperties in arbitrary adversarial contexts, which we call robust hyperproperty preservation. For this, we study the preservation of several classes of hyperproperties and for each class we propose an equivalent "property-free" characterization of secure compilation that is generally better tailored for proofs. Even the strongest of our soundness criteria, the robust preservation of all hyperproperties, seems achievable for simple transformations and provable using context back-translation techniques previously developed for showing fully abstract compilation. While proving the robust preservation of hyperproperties that are not safety requires such powerful context back-translation techniques, for preserving safety hyperproperties robustly, translating each finite trace prefix back to a source context seems to suffice
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