An Improvement of Intrusion Attack Categorization and Recognition System

Intrusion detection (ID) is a method of network security management system for computers. An IDS gathers the information from various area within a computer or a network to identify possible security breaches, which include both intrusions and misuse. ID uses vulnerability assessment, which is a method developed to assess the security of a computer system. The misuse detection, the IDS analyzes the information it gathers and compares it to large databases of attack signatures. In anomaly detection, the system administrator defines the baseline, state of the networks traffic load, breakdown, protocol, and typical packet size. In this project, we present an online updating technique for our osPCA. This updating technique allows to the efficiently calculate the approximated dominant eigenvector without performing Eigen analysis. Compared to the power Method algorithms, then the required computational costs and memory requirements are significantly reduced, and thus our method is especially preferable in online, streaming data, or large scale problems.