Kai Chen (Hong Kong University of Science and Technology), Qiang Yang (WeBank and Hong Kong University of Science and Technolo

Privacy-preserving Computing

for Big Data Analytics and AI

• Gebundenes Buch

Produktbeschreibung

Privacy-preserving computing aims to protect the personal information of users while capitalizing on the possibilities offered by big data. This practical introduction for students, researchers, and industry practitioners presents a systematic tour of recent advances in privacy-preserving methods for real-world problems in analytics and AI.

Produktdetails

• Verlag: Cambridge University Press
• Seitenzahl: 271
• Erscheinungstermin: 16. November 2023
• Englisch
• Abmessung: 157mm x 236mm x 21mm
• Gewicht: 526g
• ISBN-13: 9781009299510
• ISBN-10: 1009299514
• Artikelnr.: 68715911

Autorenporträt

Kai Chen is Professor at the Department of Computer Science and Engineering of the Hong Kong University of Science and Technology, where he leads the Intelligent Networking and Systems (iSING) Lab and the WeChat-HKUST Joint Lab on Artificial Intelligence Technology. His research interests include data center networking, high-performance networking, machine learning systems, and hardware acceleration.

Inhaltsangabe

1. Introduction to privacy-preserving computing
2. Secret sharing
3. Homomorphic encryption
4. Oblivious transfer
5. Garbled circuit
6. Differential privacy
7. Trusted execution environment
8. Federated learning
9. Privacy-preserving computing platforms
10. Case studies of privacy-preserving computing
11. Future of privacy-preserving computing
References
Index.