Improving Predictability of User-Affecting Metrics to Support Anomaly Detection in Cloud Services.
Vilc Queupe RufinoMateus Schulz NogueiraAlberto AvritzerDaniel S. MenaschéBarbara RussoAndrea JanesVincenzo FermeAndré van HoornHenning SchulzCabral LimaPublished in: CoRR (2020)
Keyphrases
- anomaly detection
- intrusion detection
- anomalous behavior
- end users
- network intrusion detection
- detecting anomalies
- network traffic
- detect anomalies
- cloud computing
- intrusion detection system
- negative selection algorithm
- normal behavior
- unsupervised learning
- user interface
- user interaction
- cloud services
- data analysis
- machine learning
- user experience
- data management