A Novel Virus Detection and Active Defense Algorithm Based on SVM Optimized by Differential Evolution Algorithm

DOI

10.2991/isrme-15.2015.14How to use a DOI?

Keywords

Differential Evolution; SVM; Active Defense; Virus Detection; Information Security.

Abstract

This paper proposes a novel active defense strategy focuses on users’ behavior patterns which to classify the behaviors accurately by SVM for virus detecting. Differential evolution was introduced to improve the precision of SVM and turns it into an optimization problem which object is the classification precision. And the parameters are regarded as the variables to be optimized. The experimental results show that the proposed model has a higher precision than the compared methods, such as BPNN, SVM, GA-SVM, etc. In addition, the method is more efficient so that, it can be quickly updated and applied.

Copyright

© 2015, 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  - Jieqing Ai
AU  - Zhenyue Long
AU  - Shang Gao
PY  - 2015/04
DA  - 2015/04
TI  - A Novel Virus Detection and Active Defense Algorithm Based on SVM Optimized by Differential Evolution Algorithm
BT  - Proceedings of the 2015 International Conference on Intelligent Systems Research and Mechatronics Engineering
PB  - Atlantis Press
SP  - 53
EP  - 56
SN  - 1951-6851
UR  - https://doi.org/10.2991/isrme-15.2015.14
DO  - 10.2991/isrme-15.2015.14
ID  - Ai2015/04
ER  -