Anomaly detecting and ranking of the cloud computing platform by multi-view learning

Author:

Zhang Jing

Publisher

Springer Science and Business Media LLC

Subject

Computer Networks and Communications,Hardware and Architecture,Media Technology,Software

Reference39 articles.

1. Baek S, Kwon D, Kim J et al (2017) Unsupervised labeling for supervised anomaly detection in enterprise and cloud networks. In: 2017 IEEE 4th international conference on cyber security and cloud computing (CSC loud). IEEE, pp 205–210

2. Dean DJ, Nguyen H, Gu X (2012) Unsupervised behavior learning for predicting performance anomalies in virtualized cloud systems. In: Proceedings of the 9th ACM international conference on autonomic computing, pp 191–200

3. Du KL, Swamy MNS (2014) Independent component analysis. Springer, London

4. Farshchi M, Schneider JG, Weber I et al (2017) Metric selection and anomaly detection for cloud operations using log and metric correlation analysis. J Syst Softw 137(5):531–549

5. Fu S (2011) Performance metric selection for autonomic anomaly detection on cloud computing systems. In: Proceedings of the global telecommunications conference. IEEE, Washington, pp 1–5

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