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.