國立虎尾科技大學 |

Privacy enhancing techniques = practices and applications /

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	Privacy enhancing techniques/ by Xun Yi ... [et al.].
其他題名:	practices and applications /
其他作者:	Yi, Xun.
出版者:	Cham :Springer Nature Switzerland : : 2025.,
面頁冊數:	xi, 254 p. :ill. (some col.), digital ; : 24 cm.;
Contained By:	Springer Nature eBook
標題:	Privacy-preserving techniques (Computer science) -
電子資源:	https://doi.org/10.1007/978-3-031-95140-4
ISBN:	9783031951404

Privacy enhancing techniques = practices and applications /
Privacy enhancing techniquespractices and applications /[electronic resource] :by Xun Yi ... [et al.]. - Cham :Springer Nature Switzerland :2025. - xi, 254 p. :ill. (some col.), digital ;24 cm.

Chapter 1: Introduction -- Chapter 2: Homomorphic Encryption -- Chapter 3: Multiparty Computation -- Chapter 4: Differential Privacy -- Chapter 5: Privacy-Preserving Data Mining -- Chapter 6: Privacy-Preserving Machine Learning -- Chapter 7: Privacy-Preserving Social Networks -- Chapter 8: Privacy-Preserving Location-Based Services -- Chapter 9: Privacy and Digital Trust -- Chapter 10: Conclusion.

This book provides a comprehensive exploration of advanced privacy-preserving methods, ensuring secure data processing across various domains. This book also delves into key technologies such as homomorphic encryption, secure multiparty computation, and differential privacy, discussing their theoretical foundations, implementation challenges, and real-world applications in cloud computing, blockchain, artificial intelligence, and healthcare. With the rapid growth of digital technologies, data privacy has become a critical concern for individuals, businesses, and governments. The chapters cover fundamental cryptographic principles and extend into applications in privacy-preserving data mining, secure machine learning, and privacy-aware social networks. By combining state-of-the-art techniques with practical case studies, this book serves as a valuable resource for those navigating the evolving landscape of data privacy and security. Designed to bridge theory and practice, this book is tailored for researchers and graduate students focused on this field. Industry professionals seeking an in-depth understanding of privacy-enhancing technologies will also want to purchase this book.

ISBN: 9783031951404

Standard No.: 10.1007/978-3-031-95140-4doiSubjects--Topical Terms:

1454935
Privacy-preserving techniques (Computer science)

LC Class. No.: QA76.9.P735 / Y5 2025

Dewey Class. No.: 005.8

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520 $a This book provides a comprehensive exploration of advanced privacy-preserving methods, ensuring secure data processing across various domains. This book also delves into key technologies such as homomorphic encryption, secure multiparty computation, and differential privacy, discussing their theoretical foundations, implementation challenges, and real-world applications in cloud computing, blockchain, artificial intelligence, and healthcare. With the rapid growth of digital technologies, data privacy has become a critical concern for individuals, businesses, and governments. The chapters cover fundamental cryptographic principles and extend into applications in privacy-preserving data mining, secure machine learning, and privacy-aware social networks. By combining state-of-the-art techniques with practical case studies, this book serves as a valuable resource for those navigating the evolving landscape of data privacy and security. Designed to bridge theory and practice, this book is tailored for researchers and graduate students focused on this field. Industry professionals seeking an in-depth understanding of privacy-enhancing technologies will also want to purchase this book.
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