• Medientyp: E-Book
  • Titel: Machine Learning for Cyber Security : Third International Conference, ML4CS 2020, Guangzhou, China, October 8–10, 2020, Proceedings, Part III
  • Beteiligte: Chen, Xiaofeng [Herausgeber:in]; Yan, Hongyang [Herausgeber:in]; Yan, Qiben [Herausgeber:in]; Zhang, Xiangliang [Herausgeber:in]
  • Erschienen: Cham: Springer International Publishing, 2020.
    Cham: Imprint: Springer, 2020.
  • Erschienen in: Security and Cryptology ; 12488
    Springer eBook Collection
  • Ausgabe: 1st ed. 2020.
  • Umfang: 1 Online-Ressource(XV, 554 p. 267 illus., 162 illus. in color.)
  • Sprache: Englisch
  • DOI: 10.1007/978-3-030-62463-7
  • ISBN: 9783030624637
  • Identifikator:
  • Schlagwörter: Computer security. ; Application software. ; Education—Data processing. ; Computer communication systems. ; Architecture, Computer. ; Machine learning. ; Social sciences ; Education ; Data protection. ; Computer networks . ; Computer systems.
  • Entstehung:
  • Anmerkungen:
  • Beschreibung: 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.