A Novel Virus Detection and Active Defense Algorithm Based on SVM Optimized by Differential Evolution Algorithm
- https://doi.org/10.2991/isrme-15.2015.14How to use a DOI?
- Differential Evolution; SVM; Active Defense; Virus Detection; Information Security.
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.
- © 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/).
Cite this article
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 - https://doi.org/10.2991/isrme-15.2015.14 ID - Ai2015/04 ER -