Privacy-Preserving Machine Learning
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 p…
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Produktdetails
Weitere Autoren: Li, Ping / Li, Tong / Chen, Xiaofeng / Liu, Zheli
- ISBN: 978-981-1691-38-6
- EAN: 9789811691386
- Produktnummer: 38563527
- Verlag: Springer Nature Singapore
- Sprache: Englisch
- Erscheinungsjahr: 2022
- Seitenangabe: 96 S.
- Masse: H23.5 cm x B15.5 cm x D0.5 cm 160 g
- Auflage: 1st ed. 2022
- Abbildungen: Paperback
- Gewicht: 160
Über den Autor
148667273
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