Outliers Detection as Network Intrusion Detection System Using Multi Layered Framework

Outlier detection is a popular technique that can be utilized for finding Intruders. Security is becoming a critical part of organizational information systems. Network Intrusion Detection System (NIDS) is an important detection system that is used as a counter measure to preserve data integrity and system availability from attacks [2]. However, current researches find that it is extremely difficult to find out outliers directly from high dimensional datasets. In our work we used entropy method for reducing high dimensionality to lower dimensionality, where the processing time can be saved without compromising the efficiency. Here we proposed a framework for finding outliers from high dimensional dataset and also presented the results. We implemented our proposed method on standard dataset kddcup'99 and the results shown with the high accuracy.