The Science of Quantitative Information Flow
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Beschreibung
This book presents a comprehensive mathematical theory that explains precisely what information flow is, how it can be assessed quantitatively – so bringing precise meaning to the intuition that certain information leaks are small enough to be tolerated – and how systems can be constructed that achieve rigorous, quantitative information-flow guarantees in those terms. It addresses the fundamental challenge that functional and practical requirements frequently conflict with the goal of preserving confidentiality, making perfect security unattainable.
Topics include: a systematic presentation of how unwanted information flow, i.e., "leaks", can be quantified in operationally significant ways and then bounded, both with respect to estimated benefit for an attacking adversary and by comparisons between alternative implementations; a detailed study of capacity, refinement, and Dalenius leakage, supporting robust leakage assessments; a unification of information-theoretic channels and information-leaking sequential programs within the same framework; and a collection of case studies, showing how the theory can be applied to interesting realistic scenarios.
The text is unified, self-contained and comprehensive, accessible to students and researchers with some knowledge of discrete probability and undergraduate mathematics, and contains exercises to facilitate its use as a course textbook.
This book presents a comprehensive mathematical theory that explains precisely what information flow is, how it can be assessed quantitatively – so bringing precise meaning to the intuition that certain information leaks are small enough to be tolerated – and how systems can be constructed that achieve rigorous, quantitative information-flow guarantees in those terms. It addresses the fundamental challenge that functional and practical requirements frequently conflict with the goal of preserving confidentiality, making perfect security unattainable.
Topics include: a systematic presentation of how unwanted information flow, i.e., "leaks", can be quantified in operationally significant ways and then bounded, both with respect to estimated benefit for an attacking adversary and by comparisons between alternative implementations; a detailed study of capacity, refinement, and Dalenius leakage, supporting robust leakage assessments; a unification of information-theoretic channels and information-leaking sequential programs within the same framework; and a collection of case studies, showing how the theory can be applied to interesting realistic scenarios.The text is unified, self-contained and comprehensive, accessible to students and researchers with some knowledge of discrete probability and undergraduate mathematics, and contains exercises to facilitate its use as a course textbook.Computer systems that process sensitive information should preserve that information's confidentiality, but our current cyber-infrastructure is failing to achieve this goal: reports of massive-scale information disclosures are distressingly frequent Written by an international team of six experts, with diverse research backgrounds, whose work was recognized with the NSA's Best Scientific Cybersecurity Paper Award in 2015 and the ETAPS 2020 Test of Time Award Unified, self-contained, and comprehensive presentation, with numerous exercises, suitable for students and researchers
Autor*in
Mário S. Alvim
Themen in »The Science of Quantitative Information Flow«
Computer Security Disorder Measures Hidden Markov Models (HMMs) Information Flow Information Theory Program Semantics Static Analysis Vulnerability Measures