This book offers a novel approach to data privacy by unifying side-channel attacks within a general conceptual framework. This book then applies the framework in three concrete domains. First, the book examines privacy-preserving data publishing with publicly-known algorithms, studying a generic strategy independent of data utility measures and syntactic privacy properties before discussing an extended approach to improve the efficiency. Next, the book explores privacy-preserving traffic padding in Web applications, first via a model to quantify privacy and cost and then by introducing randomness to provide background knowledge-resistant privacy guarantee. Finally, the book considers privacy-preserving smart metering by proposing a light-weight approach to simultaneously preserving users' privacy and ensuring billing accuracy. Designed for researchers and professionals, this book is also suitable for advanced-level students interested in privacy, algorithms, or web applications.

Preserving Privacy Against Side-Channel Leaks: From Data Publishing to Web Applications (Advances in Information Security, 68)

Liu, Wen Ming

Wang, Lingyu

Reference

Springer

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Books by Liu, Wen Ming

See the best price to sell, buy, or rent books by Liu, Wen Ming. BookScouter helps to compare book prices from 25+ online bookstores and 30+ buyback vendors with a single search.

Preserving Privacy Against Side-Channel Leaks: From Data Publishing to Web Applications (Advances in Information Security, 68)

Preserving Privacy Against Side-Channel Leaks: From Data Publishing to Web Applications (Advances in Information Security, 68)