The Application of Rough Sets on Network Intrusion Detection

With a growing amount of network information flowing, the limitations of the traditional network IDSs become more and more obvious, which can not adapt to the increasing trend of novel network attacks and data quantities. As a result, the analysis process becomes time-consuming. Fortunately, as is well known, rough set's reduction theory can effectively avoid redundancy and reduce extra attributes. Therefore, to solve the problems in IDSs, the paper advocates using the theory of rough set to improve the attribute reduction algorithm. Experimental results show that the number of attributes can be reduced 64% using the proposed method. Thus, it can be concluded that the presented method can shorten detection process efficiently.