Privacy-preserving computing for big data analytics and AI /
"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 meth...
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Main Authors: | |
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Group Author: | |
Published: |
Cambridge University Press,
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Publisher Address: | Cambridge, United Kingdom : |
Publication Dates: | 2024. |
Literature type: | Book |
Language: | English |
Subjects: | |
Summary: |
"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"-- |
Carrier Form: | xii, 255 pages : illustrations ; 24 cm |
Bibliography: | Includes bibliographical references (pages 238-252) and index. |
ISBN: |
9781009299510 1009299514 |
Index Number: | QA76 |
CLC: | TP309 |
Call Number: | TP309/C518 |
Contents: | Introduction to privacy-preserving computing -- Secret sharing -- Homomorphic encryption -- Oblivious transfer -- Garbled circuit -- Differential privacy -- Trusted execution environment -- Federated learning -- Privacy-preserving computing platforms -- Case studies of privacy-preserving computing -- Future of privacy-preserving computing. |