A Novel Approach for Intrusion Detection
Research in the field of computer and network science demands for tools and methodology to test their security effectively. Intrusion Detection System is used to perform the same with a fact that an intruder's behavior will be noticeably different from that of a legitimate user and would exploit security vulnerabilities. Proposed here is a novel intrusion detection approach with the application of Generalized Regression Neural Network and the MIT's KDD Cup 99 dataset. The result clearly demonstrates an efficient way for intrusion feature selection and detection and promises a good scope for further research.