{"product_id":"preserving-privacy-against-side-channel-leaks-from-data-publishing-to-web-applications-9783319826264","title":"Preserving Privacy Against Side-Channel Leaks: From Data Publishing to Web Applications","description":"\u003cp\u003e • Author(s): Wen Ming Liu\u003cbr\u003e • Publisher: Springer\u003cbr\u003e • Publisher Imprint: Springer\u003cbr\u003e • BISAC: Security - Cryptography \u0026amp; Encryption\u003c\/p\u003e\u003cp\u003e\u003c\/p\u003e\u003cp\u003e\u003cb\u003eFrom the Back Cover\u003c\/b\u003e\u003cbr\u003eThis 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.\u003c\/p\u003e","brand":"Springer","offers":[{"title":"Paperback","offer_id":45279156699287,"sku":"9783319826264","price":7345.0,"currency_code":"INR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0666\/3471\/1191\/files\/9783319826264.webp?v=1769292836","url":"https:\/\/atlanticbooks.com\/products\/preserving-privacy-against-side-channel-leaks-from-data-publishing-to-web-applications-9783319826264","provider":"Atlantic Books","version":"1.0","type":"link"}