LEADER 03249nam 22006015 450 001 9910993945703321 005 20251113180929.0 010 $a9789811691393 010 $a9811691398 010 $a9789811691386 010 $a981169138X 024 7 $a10.1007/978-981-16-9139-3 035 $a(CKB)5720000000228513 035 $a(DE-He213)978-981-16-9139-3 035 $a(EXLCZ)995720000000228513 100 $a20220314d2022 u| 0 101 0 $aeng 135 $aurnn#008mamaa 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aPrivacy-Preserving Machine Learning /$fby Jin Li, Ping Li, Zheli Liu, Xiaofeng Chen, Tong Li 205 $a1st ed. 2022. 210 1$aSingapore :$cSpringer Nature Singapore :$cImprint: Springer,$d2022. 215 $a1 online resource (VIII, 88 p. 21 illus., 18 illus. in color.) 225 1 $aSpringerBriefs on Cyber Security Systems and Networks,$x2522-557X 311 08$aPrint version: Li, Jin Privacy-Preserving Machine Learning Singapore : Springer Singapore Pte. Limited,c2022 9789811691386 311 08$a981169138X 327 $aIntroduction -- Secure Cooperative Learning in Early Years -- Outsourced Computation for Learning -- Secure Distributed Learning -- Learning with Differential Privacy -- Applications - Privacy-Preserving Image Processing -- Threats in Open Environment -- Conclusion. 330 $aThis book provides a thorough overview of the evolution of privacy-preserving machine learning schemes over the last ten years, after discussing the importance of privacy-preserving techniques. In response to the diversity of Internet services, data services based on machine learning are now available for various applications, including risk assessment and image recognition. In light of open access to datasets and not fully trusted environments, machine learning-based applications face enormous security and privacy risks. In turn, it presents studies conducted to address privacy issues and a series of proposed solutions for ensuring privacy protection in machine learning tasks involving multiple parties. In closing, the book reviews state-of-the-art privacy-preserving techniques and examines the security threats they face. 410 0$aSpringerBriefs on Cyber Security Systems and Networks,$x2522-557X 606 $aData protection$xLaw and legislation 606 $aMachine learning 606 $aPrivacy 606 $aMachine Learning 615 0$aData protection$xLaw and legislation. 615 0$aMachine learning. 615 14$aPrivacy. 615 24$aMachine Learning. 676 $a005.8 676 $a323.448 700 $aLi$b Jin$4aut$4http://id.loc.gov/vocabulary/relators/aut$01263437 702 $aLi$b Ping$4aut$4http://id.loc.gov/vocabulary/relators/aut 702 $aLiu$b Zheli$4aut$4http://id.loc.gov/vocabulary/relators/aut 702 $aChen$b Xiaofeng$4aut$4http://id.loc.gov/vocabulary/relators/aut 702 $aLi$b Tong$4aut$4http://id.loc.gov/vocabulary/relators/aut 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910993945703321 996 $aPrivacy-preserving machine learning$93558816 997 $aUNINA