Intrusion detection using dimensionality reduced soft matrix

The task of identifying attacks in the real time networks has become a recent point of focus in network security. A classifier performance depends on the input data. Preprocessing dataset fed as input for classifier is usually required to make the dataset suitable for efficient processing. Preprocessing is first stage of transforming data for better data representation. Dimensionality reduction is usually applied on datasets to reduce the space and time complexities and to facilitate easy handling of large datasets. This paper gives an approach for performing dimensionality reduction of input dataset. The resulting one is the soft matrix. This dimensional reduced input dataset is fed as input to classifier. The paper restricts to outlining the algorithm of proposed approach.