A Combination of Clonal Selection Algorithm and Artificial Neural Networks for Virus Detection
In this paper, we proposed a new approach using bio-inspired algorithms such as Clonal Selection Algorithm (CLONALG) and Artificial Neural Networks (ANNs) which aims to handle virus detection problem. The point of difference is using ANNs as the detectors and CLONALG as the algorithm for finding the best ANN’s structure and weights. According to experimental results, the proposed model has an acceptable detection rate and false positive rate.
KeywordsArtificial Immune System (AIS) Artificial Neural Network (ANN) Clonal Selection Algorithm (CLONALG) Virus Detection System (VDS)
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- 1.Dasgupta, D., Niño, L.F.: Immunological Computation - Theory and Applications, pp. 27–29. CRC Press (2009)Google Scholar
- 5.Doumas, A., Mavroudakis, K., Gritzalis, D., Katsikas, S.: Design of a Neural Network for Recognition and Classification of Computer Viruses. Computers & Security 14(5) (1995)Google Scholar
- 6.Chao, R., Tan, Y.: A Virus Detection System Based on AIS. In: Proceedings of the 2009 International Conference on Computational Intelligence & Security, vol. 1, pp. 6–10 (2009)Google Scholar
- 7.Daoud, E.A.: Metamorphic Viruses Detection Using Artificial Immune System. In: International Conference on Communication Software and Networks, pp. 168–172 (2009)Google Scholar
- 8.Golovko, V., Komar, M., Sachenko, A.: Principles of Neural Network Artificial Immune System Design to Detect Attacks on Computers. Modern Problems of Radio Engineering, Telecommunications and Computer Science (2010)Google Scholar