プライバシー保全コンピューティング：ビッグデータ解析とＡＩのために Privacy-preserving Computing : for Big Data Analytics and AI

Chen, Kai/ Yang, Qiang

Cambridge University Press（2023/11発売）

Cambridge University Press（2023/11発売）

• 製本 Hardcover:ハードカバー版／ページ数 271 p.
• 言語 ENG
• 商品コード 9781009299510
• DDC分類 005.8

Full Description

Privacy-preserving computing aims to protect the personal information of users while capitalizing on the possibilities unlocked by big data. This practical introduction for students, researchers, and industry practitioners is the first cohesive and systematic presentation of the field's advances over four decades. The book shows how to use privacy-preserving computing in real-world problems in data analytics and AI, and includes applications in statistics, database queries, and machine learning. The book begins by introducing cryptographic techniques such as secret sharing, homomorphic encryption, and oblivious transfer, and then broadens its focus to more widely applicable techniques such as differential privacy, trusted execution environment, and federated learning. The book ends with privacy-preserving computing in practice in areas like finance, online advertising, and healthcare, and finally offers a vision for the future of the field.

Contents

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.