Information Hiding in Probabilistic Concurrent Systems

@article{Andrs2010InformationHI,
  title={Information Hiding in Probabilistic Concurrent Systems},
  author={Miguel E. Andr{\'e}s and Catuscia Palamidessi and Peter van Rossum and Ana Sokolova},
  journal={2010 Seventh International Conference on the Quantitative Evaluation of Systems},
  year={2010},
  pages={17-26}
}
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42 Citations
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4
Background Citations
17
Methods Citations
8
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Information Hiding in Probabilistic Concurrent Systems (journal version)
TLDR
This work proposes a milder restriction on the schedulers, and defines the notion of strong (probabilistic) information hiding under various notions of observables, and proposes a method to verify that a system satisfies the property of strong information hiding, namely strong anonymity or non-interference, depending on the context.
Compositional methods for information-hiding †
TLDR
This work characterize constructs that have the property of not decreasing the degree of protection, and that can therefore be considered safe in the modular construction of systems concerned with information hiding, and derives Chaum's strong anonymity result.
Compositional Methods for Information-Hiding
TLDR
A probabilistic process calculus approach is considered to the specification of protocols for information-hiding, and constructs that have the property of not decreasing the degree of protection are characterized that can therefore be considered safe in the modular construction of protocols.
Formal Verification of Differential Privacy in Concurrent Systems. (Ve'rification formelle de la vie prive'e dans les systèmes concurrents)
TLDR
This dissertation is devoted to the development of novel reasoning techniques for verifying differential privacy in concurrent systems and presents an extension of the bisimulation metric based on the Kantorovich distance, suitable to capture a vast range of properties, including differential privacy.
Probability and hiding in concurrent processes
TLDR
This thesis addresses two problems regarding concurrent processes that exhibit both hidden and Probabilistic behaviour, or probabilistic processes for short, and proposes integrating the information, based on which a nondeterministic choice is resolved, in labels on the nondeterminism transitions.
Metrics for Differential Privacy in Concurrent Systems
TLDR
It is shown that the metrical closeness of automata guarantees the preservation of differential privacy, which makes the two metrics suitable for verification, and that process combinators are non-expansive in this pseudometric framework.
Safe Equivalences for Security Properties
TLDR
A formalism is presented in which one can specify admissible schedulers and, correspondingly, safe versions of these equivalences, and it is proved that safe bisimulation is still a congruence.
Quantitative Analysis of Information Leakage in Probabilistic and Nondeterministic Systems
TLDR
This thesis addresses the foundational aspects of formal methods for applications in security and in particular in anonymity, and develops frameworks for the specification of anonymity properties and proposes algorithms for their verification.
Confidentiality for Probabilistic Multi-threaded Programs and Its Verification
TLDR
A new notion of confidentiality for Probabilistic and non-probabilistic multi-threaded programs, formalized as scheduler-specific probabilistic observational determinism (SSPOD), together with verification methods are proposed.
A Multiplicative Variant of the Kantorovich distance for Differential Privacy
TLDR
This paper investigates techniques for proving differential privacy in the context of concurrent systems containing both probabilistic and non-deterministic behavior, and proposes a multiplicative variant of the Kantorovich-based bisimulation pseudometric which can be characterized in the form of programming problem as well as 1-Lipschitz function.
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References

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Information Hiding in Probabilistic Concurrent Systems (journal version)
TLDR
This work proposes a milder restriction on the schedulers, and defines the notion of strong (probabilistic) information hiding under various notions of observables, and proposes a method to verify that a system satisfies the property of strong information hiding, namely strong anonymity or non-interference, depending on the context.
Compositional Methods for Information-Hiding
TLDR
A probabilistic process calculus approach is considered to the specification of protocols for information-hiding, and constructs that have the property of not decreasing the degree of protection are characterized that can therefore be considered safe in the modular construction of protocols.
On the Bayes risk in information-hiding protocols
TLDR
A constructive characterization of a convex base of the probability of error is presented, which allows us to compute its maximum value (over all possible input distributions), and to identify upper bounds for it in terms of simple functions.
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TLDR
This paper argues that the consensus definitions of Shannon entropy actually fail to give good security guarantees, and explores an alternative foundation based on a concept of vulnerability and which measures uncertainty using Renyi's min-entropy , rather than Shannon entropy.
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TLDR
This work gives several definitions of anonymity with respect to agents, actions, and observers in multiagent systems, and relates these definitions to other definitions of information hiding, such as secrecy.
Probabilistic anonymity via coalgebraic simulations
Safe Equivalences for Security Properties
TLDR
A formalism is presented in which one can specify admissible schedulers and, correspondingly, safe versions of these equivalences, and it is proved that safe bisimulation is still a congruence.
Making random choices invisible to the scheduler
Entropy measures and unconditional security in cryptography
TLDR
Information-theoretic meth¬ ods are used for proving the security of unconditionally secure cryptosystems, and a new information measure, smooth entropy, is introduced to quantify the number of almost uniform random bits that can be extracted from a source by probabilistic algorithms.
Quantitative Notions of Leakage for One-try Attacks
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