Jin Li

(Author)

Privacy-Preserving Machine Learning (2022)Paperback - 2022, 15 March 2022

Privacy-Preserving Machine Learning (2022)
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Part of Series
Springerbriefs on Cyber Security Systems and Networks
Print Length
88 pages
Language
English
Publisher
Springer
Date Published
15 Mar 2022
ISBN-10
981169138X
ISBN-13
9789811691386

Description

This book provides a thorough overview of the evolution of privacy-preserving machine learning schemes over the last ten years, after discussing the importance of privacy-preserving techniques. In response to the diversity of Internet services, data services based on machine learning are now available for various applications, including risk assessment and image recognition. In light of open access to datasets and not fully trusted environments, machine learning-based applications face enormous security and privacy risks. In turn, it presents studies conducted to address privacy issues and a series of proposed solutions for ensuring privacy protection in machine learning tasks involving multiple parties. In closing, the book reviews state-of-the-art privacy-preserving techniques and examines the security threats they face.

Product Details

Authors:
Jin LiPing LiZheli LiuXiaofeng ChenTong Li
Book Edition:
2022
Book Format:
Paperback
Country of Origin:
NL
Date Published:
15 March 2022
Dimensions:
23.39 x 15.6 x 0.51 cm
ISBN-10:
981169138X
ISBN-13:
9789811691386
Language:
English
Location:
Singapore
Pages:
88
Publisher:
Weight:
149.69 gm

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