"Evaluation of Machine Learning Algorithms for Anomaly Detection."

Nebrase Elmrabit et al. (2020)

> Home

Details and statistics

DOI: 10.1109/CYBERSECURITY49315.2020.9138871

access: closed

type: Conference or Workshop Paper

metadata version: 2022-10-02

- view
  - electronic edition via DOI
  - unpaywalled version
  authority control:
- export record
  dblp key:
  - conf/cybersecpods/ElmrabitZL020
- ask others
- share record
  persistent URL:
  - https://dblp.org/rec/conf/cybersecpods/ElmrabitZL020
Nebrase Elmrabit, Feixiang Zhou, Fengyin Li, Huiyu Zhou:
Evaluation of Machine Learning Algorithms for Anomaly Detection. Cyber Security 2020: 1-8

manage site settings

To protect your privacy, all features that rely on external API calls from your browser are turned off by default. You need to opt-in for them to become active. All settings here will be stored as cookies with your web browser. For more information see our F.A.Q.