On the effectiveness of isolation-based anomaly detection in cloud data centers.
Rodrigo N. CalheirosKotagiri RamamohanaraoRajkumar BuyyaChristopher LeckieSteve VersteegPublished in: Concurr. Comput. Pract. Exp. (2017)
Keyphrases
- anomaly detection
- data center
- cloud computing
- intrusion detection
- detecting anomalies
- anomalous behavior
- network intrusion detection
- power consumption
- virtual machine
- cost effective
- network traffic
- network anomaly detection
- intrusion detection system
- multi tenant
- detecting anomalous
- unsupervised anomaly detection
- energy efficiency
- one class support vector machines
- energy consumption
- carbon dioxide
- network security
- detect anomalies
- unsupervised learning
- negative selection algorithm
- databases
- service providers
- cloud services
- data management
- network intrusion
- computing resources
- learning algorithm
- machine learning
- cumulative sum