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A Per Model of Secure Information Flow in Sequential Programs
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CONCUR '00 Proceedings of the 11th International Conference on Concurrency Theory
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INDOCRYPT '00 Proceedings of the First International Conference on Progress in Cryptology
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Abstraction, Refinement And Proof For Probabilistic Systems (Monographs in Computer Science)
Abstraction, Refinement And Proof For Probabilistic Systems (Monographs in Computer Science)
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Mathematical Structures in Computer Science
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CSF '07 Proceedings of the 20th IEEE Computer Security Foundations Symposium
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Electronic Notes in Theoretical Computer Science (ENTCS)
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Electronic Notes in Theoretical Computer Science (ENTCS)
The Kantorovich Metric in Computer Science: A Brief Survey
Electronic Notes in Theoretical Computer Science (ENTCS)
Planning and acting in partially observable stochastic domains
Artificial Intelligence
Equivalence relations in fully and partially observable Markov decision processes
IJCAI'09 Proceedings of the 21st international jont conference on Artifical intelligence
Compositional methods for information-hiding
FOSSACS'08/ETAPS'08 Proceedings of the Theory and practice of software, 11th international conference on Foundations of software science and computational structures
Adversaries and information leaks (Tutorial)
TGC'07 Proceedings of the 3rd conference on Trustworthy global computing
Quantitative Information Flow - Verification Hardness and Possibilities
CSF '10 Proceedings of the 2010 23rd IEEE Computer Security Foundations Symposium
Compositional closure for Bayes Risk in probabilistic noninterference
ICALP'10 Proceedings of the 37th international colloquium conference on Automata, languages and programming: Part II
Elementary probability theory in the eindhoven style
MPC'12 Proceedings of the 11th international conference on Mathematics of Program Construction
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We propose a novel domain-theoretic model for nondeterminism, probability and hidden state, with relations on it that compare information flow. One relation is Smyth-like, based on a structural, refinement-like order between semantic elements; the other is a testing order that generalises several extant entropy-based techniques. Our principal theorem is that the two orders are equivalent. The model is based on the Giry/Kantorovich monads, and it abstracts Partially Observable Markov Decision Processes by discarding observables' actual values but retaining the effect they had on an observer's knowledge. We illustrate the model, and its orders, on some small examples, where we find that our formalism provides the apparatus for comparing systems in terms of the information they leak.