國立高雄大學圖資館 |

登入

回首頁 到查詢結果 [ subject:"Machine Learning." ]

Privacy-preserving machine learning

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Privacy-preserving machine learningby Jin Li ... [et al.].
其他作者:	Li, Jin.
出版者:	Singapore :Springer Singapore :2022.
面頁冊數:	viii, 88 p. :ill. (some col.), digital ;24 cm.
Contained By:	Springer Nature eBook
標題:	Machine learningSecurity measures.
電子資源:	https://doi.org/10.1007/978-981-16-9139-3
ISBN:	9789811691393$q(electronic bk.)

Privacy-preserving machine learning
Privacy-preserving machine learning[electronic resource] /by Jin Li ... [et al.]. - Singapore :Springer Singapore :2022. - viii, 88 p. :ill. (some col.), digital ;24 cm. - SpringerBriefs on cyber security systems and networks,2522-557X. - SpringerBriefs on cyber security systems and networks..

Introduction -- 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.

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.

ISBN: 9789811691393$q(electronic bk.)

Standard No.: 10.1007/978-981-16-9139-3doiSubjects--Topical Terms:

897594
Machine learning
--Security measures.

LC Class. No.: Q325.5

Dewey Class. No.: 006.31

Privacy-preserving machine learning
LDR:02145nmm a2200337 a 4500 001 622363
003 DE-He213
005 20220314024648.0
006 m d
007 cr nn 008maaau
008 221209s2022 si s 0 eng d
020 $a 9789811691393$q(electronic bk.)
020 $a 9789811691386$q(paper)
024 7 $a 10.1007/978-981-16-9139-3 $2 doi
035 $a 978-981-16-9139-3
040 $a GP $c GP
041 0 $a eng
050 4 $a Q325.5
072 7 $a URD $2 bicssc
072 7 $a COM060040 $2 bisacsh
072 7 $a URD $2 thema
082 0 4 $a 006.31 $2 23
090 $a Q325.5 $b .P961 2022
245 0 0 $a Privacy-preserving machine learning $h [electronic resource] / $c by Jin Li ... [et al.].
260 $a Singapore : $b Springer Singapore : $b Imprint: Springer, $c 2022.
300 $a viii, 88 p. : $b ill. (some col.), digital ; $c 24 cm.
490 1 $a SpringerBriefs on cyber security systems and networks, $x 2522-557X
505 0 $a Introduction -- 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.
520 $a 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.
650 0 $a Machine learning $x Security measures. $3 897594
650 1 4 $a Privacy. $3 268519
650 2 4 $a Machine Learning. $3 833608
700 1 $a Li, Jin. $3 825736
710 2 $a SpringerLink (Online service) $3 273601
773 0 $t Springer Nature eBook
830 0 $a SpringerBriefs on cyber security systems and networks. $3 814707
856 4 0 $u https://doi.org/10.1007/978-981-16-9139-3
950 $a Computer Science (SpringerNature-11645)