Exploring a Novel Approach for providing Software Security Using Soft Computing Systems

Most of the Soft Computing algorithms will learn from human knowledge and mimic human skills. We survey the principal constituents of soft computing techniques including Fuzzy Logic, Artificial Neural Networks, Support Vector Machines, Probabilistic Reasoning, Genetic Algorithms and Multi-Variate Adaptive Regressive Splines. Soft Computing techniques are being widely used by the IDS community due to their generalization capabilities that help in detecting known and unknown intrusions or the attacks that have no previously described patterns. Due to increasing incidents of cyber attacks, building effective intrusion detection systems(IDSs) are essential for protecting information systems security. This paper describes the use of soft computing techniques to detect the unknown intrusions and evidences that soft computing technique is better than previous used techniques to detect the intrusions.