{"product_id":"privacy-in-vehicular-networks-baihe-ma-9781032823522","title":"Privacy in Vehicular Networks: Challenges and Solutions","description":"\u003cp\u003eIn an era where vehicular networks and Location-Based Services (LBS) are rapidly expanding, safeguarding location privacy has become a critical challenge.\u003ci\u003e Privacy in Vehicular Networks\u003c\/i\u003e delves into the complexities of protecting sensitive location data within the dynamic and decentralized environment of vehicular networks. This book stands out by addressing both the theoretical and practical aspects of location privacy, offering a thorough analysis of existing vulnerabilities and innovative solutions.\u003c\/p\u003e\u003cp\u003eThis book meticulously examines the interplay between location privacy and the operational necessities of road networks. It introduces a differential privacy framework tailored specifically for vehicular environments, ensuring robust protection against various types of privacy breaches. By integrating advanced detection algorithms and personalized obfuscation schemes, the book provides a multi-faceted approach to enhancing location privacy without compromising data utility.\u003c\/p\u003e\u003cp\u003eThe key features of this book can be summarized as follows: \u003c\/p\u003e\u003cul\u003e \u003cli\u003e \u003cstrong\u003eComprehensive Analysis: \u003c\/strong\u003e Detailed examination of location privacy requirements and existing preservation mechanisms\u003c\/li\u003e \u003cli\u003e \u003cstrong\u003eInnovative Solutions: \u003c\/strong\u003e Introduction of a Personalized Location Privacy-Preserving (PLPP) mechanism based on Road Network-Indistinguishability (RN-I)\u003c\/li\u003e \u003cli\u003e \u003cstrong\u003eAdvanced Detection: \u003c\/strong\u003e Utilization of Convolutional Neural Networks (CNN) for detecting illegal trajectories and enhancing data integrity\u003c\/li\u003e \u003cli\u003e \u003cstrong\u003eCollective Security: \u003c\/strong\u003e Implementation of the Cloaking Region Obfuscation (CRO) mechanism to secure multiple vehicles in high-density road networks\u003c\/li\u003e \u003cli\u003e \u003cstrong\u003eHolistic Approach: \u003c\/strong\u003e Joint Trajectory Obfuscation and Pseudonym Swapping (JTOPS) mechanism to seamlessly integrate privacy preservation with traffic management\u003c\/li\u003e \u003cli\u003e \u003cstrong\u003eFuture-Ready: \u003c\/strong\u003e Exploration of upcoming challenges and recommendations for future research in vehicular network privacy\u003c\/li\u003e \u003c\/ul\u003e\u003cp\u003eThis book is essential for researchers, practitioners, and policymakers in the fields of vehicular networks, data privacy, and cybersecurity. It provides valuable insights for anyone involved in the development and implementation of LBS, ensuring they are equipped with the knowledge to protect user privacy effectively.\u003c\/p\u003e\u003cbr\u003e\u003cbr\u003e\u003cb\u003eAuthor:\u003c\/b\u003e Baihe Ma, Xu Wang, Wei Ni\u003cbr\u003e\u003cb\u003eISBN-10:\u003c\/b\u003e 1032823526\u003cbr\u003e\u003cb\u003eISBN-13:\u003c\/b\u003e 9781032823522\u003cbr\u003e\u003cb\u003ePublisher:\u003c\/b\u003e CRC Press\u003cbr\u003e\u003cb\u003eLanguage:\u003c\/b\u003e English\u003cbr\u003e\u003cb\u003ePublished:\u003c\/b\u003e 02\/18\/2025\u003cbr\u003e\u003cb\u003ePages:\u003c\/b\u003e 174\u003cbr\u003e\u003cb\u003eFormat:\u003c\/b\u003e Hardcover\u003cbr\u003e\u003cb\u003eWeight:\u003c\/b\u003e 1.20lbs\u003cbr\u003e\u003cb\u003eSize:\u003c\/b\u003e 10.00h x 7.00w x 0.50d","brand":"Baihe Ma","offers":[{"title":"Hardcover","offer_id":46721460338943,"sku":"9781032823522","price":160.0,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0662\/2982\/9887\/files\/img_3ffdb8c5-23b8-4a42-abe5-f66904879c10.jpg?v=1742752933","url":"https:\/\/www.whiterainbookhouse.com\/products\/privacy-in-vehicular-networks-baihe-ma-9781032823522","provider":"WR Book House","version":"1.0","type":"link"}