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Privacy-Preserving Deep Learning: A Comprehensive Survey - SpringerBriefs on Cyber Security Systems and Networks 2021 edition
Kwangjo Kim
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Privacy-Preserving Deep Learning: A Comprehensive Survey - SpringerBriefs on Cyber Security Systems and Networks 2021 edition
Kwangjo Kim
This book discusses the state-of-the-art in privacy-preserving deep learning (PPDL), especially as a tool for machine learning as a service (MLaaS), which serves as an enabling technology by combining classical privacy-preserving and cryptographic protocols with deep learning.
74 pages, 14 Illustrations, color; 7 Illustrations, black and white; XIV, 74 p. 21 illus., 14 illus.
| Medie | Bøger Paperback Bog (Bog med blødt omslag og limet ryg) |
| Udgivet | 23. juli 2021 |
| ISBN13 | 9789811637636 |
| Forlag | Springer Verlag, Singapore |
| Antal sider | 74 |
| Mål | 152 g |
![Cover for Kwangjo Kim · Network Intrusion Detection using Deep Learning: A Feature Learning Approach - SpringerBriefs on Cyber Security Systems and Networks (Paperback Bog) [1st ed. 2018 edition] (2018)](https://imusic.b-cdn.net/images/item/original/438/9789811314438.jpg?kwangjo-kim-2018-network-intrusion-detection-using-deep-learning-a-feature-learning-approach-springerbriefs-on-cyber-security-systems-and-networks-paperback-bog&class=scaled&v=1541782700)
