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Backdoor Detection System Using Artificial Neural Network and Genetic Algorithm

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2 Author(s)

In this paper, we consider the issue of detecting a missing member of malicious codes named backdoors. We developed a novel approach for revealing them based on two clustered, system behavior and network traffic. Backdoors can easily be installed on the victim system aiming its exploit, detecting them requires considerable policies. Using Artificial Intelligence (AI) has revolutionized all security providing systems. Hence, our proposed method acquired a tunable idea using Artificial Neural Network (ANN) for classifying system features and predicting the percentage of backdoor existing probability and Genetic Algorithm (GA) in order to give a deterministic answer to the issue. Using ANN incorporation with the GA guarantees how precise our approach could be.

Published in:

Computational and Information Sciences (ICCIS), 2011 International Conference on

Date of Conference:

21-23 Oct. 2011