Privacy Enhancing Techniques - Andrei Kelarev

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Résumé :

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....

Biographie:
Xun Yi is a Professor with the School of Computing Technologies, RMIT University, Australia. His research interests include data privacy protection, cloud and IoT security, blockchain, network security, and applied cryptography. He has published over 300 research papers in international journals and conference proceedings. He serves as an Associate Editor for IEEE Transactions on Dependable and Secure Computing, IEEE Transactions on Knowledge and Data Engineering, ACM Computing Surveys, and Information Sciences. Xuechao Yang is a Lecturer at the School of Computing Technologies, RMIT University, Australia. He holds a bachelor&rsquo...

Sommaire:
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....