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Chen, Xiaofeng [Editor]; Yan, Hongyang [Editor]; Yan, Qiben [Editor]; Zhang, Xiangliang [Editor]

Machine Learning for Cyber Security - [1st ed. 2020.]

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  • Media type: E-Book
  • Title: Machine Learning for Cyber Security : Third International Conference, ML4CS 2020, Guangzhou, China, October 8–10, 2020, Proceedings, Part I
  • Contributor: Chen, Xiaofeng [Editor]; Yan, Hongyang [Editor]; Yan, Qiben [Editor]; Zhang, Xiangliang [Editor]
  • Published: Cham: Springer International Publishing, 2020.
    Cham: Imprint: Springer, 2020.
  • Published in: Security and Cryptology ; 12486
    Springer eBook Collection
  • Issue: 1st ed. 2020.
  • Extent: 1 Online-Ressource(XXVII, 650 p. 282 illus., 183 illus. in color.)
  • Language: English
  • DOI: 10.1007/978-3-030-62223-7
  • ISBN: 9783030622237
  • Identifier:
  • Keywords: Computer security. ; Application software. ; Education—Data processing. ; Computers and civilization. ; Data encryption (Computer science). ; Education ; Data protection. ; Cryptography. ; Social sciences
  • Origination:
  • Footnote:
  • Description: Machine learning -- Security. Privacy-preserving -- Cyber security -- Adversarial machine Learning -- Malware detection and analysis -- Data mining -- AI.

    This three volume book set constitutes the proceedings of the Third International Conference on Machine Learning for Cyber Security, ML4CS 2020, held in Xi’an, China in October 2020. The 118 full papers and 40 short papers presented were carefully reviewed and selected from 360 submissions. The papers offer a wide range of the following subjects: Machine learning, security, privacy-preserving, cyber security, Adversarial machine Learning, Malware detection and analysis, Data mining, and Artificial Intelligence.