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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.
