Research on Algorithm of Dependability Oriented Anomaly Detection of Virtual Machines under Cloud

DOI

10.2991/ameii-16.2016.215How to use a DOI?

Keywords

Cloud Platforms, Anomaly Detection of VMs, Kernel Metod, Principal component analysis (PCA), Feature Extraction

Abstract

In this paper, a large-scale cloud platform Virtual machine anomaly detection key technologies. For cloud environments systematic study of the feature extraction technique is proposed based on principal component analysis (PCA) for feature extraction algorithm. The algorithm selects the most efficient or concentrated extract from the original performance, data analysis most useful "features", the first analysis of the anomaly detection problem to be solved.

Copyright

© 2016, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Hongli Li
PY  - 2016/04
DA  - 2016/04
TI  - Research on Algorithm of Dependability Oriented Anomaly Detection of Virtual Machines under Cloud
BT  - Proceedings of the 2nd International Conference on Advances in Mechanical Engineering and Industrial Informatics (AMEII 2016)
PB  - Atlantis Press
SP  - 1132
EP  - 1137
SN  - 2352-5401
UR  - https://doi.org/10.2991/ameii-16.2016.215
DO  - 10.2991/ameii-16.2016.215
ID  - Li2016/04
ER  -