Research on IDS Snort Based on Classic Clustering Algorithm

Abstract

With the rapid development of the Internet, the “Internet +” model has been widely used. A new generation of security technology such as intrusion detection is urgently needed to ensure information security. In order to improve the detection efficiency of intrusion detection, IDS Snort research based on the classic clustering algorithm was performed. First, the traditional clustering algorithm, Kmeans algorithm, itself has some uncertain factors. The algorithm is optimized to make it better used in IDS Snort. Second, Combining the improved Kmeans algorithm with intrusion detection technology to improve Snort and analyze the advantages of applied to IDS Snort. Finally, the experimental results show that compared with the traditional Snort, the improved Snort has a significantly improved detection efficiency, which makes the intrusion detection technology further and the information security more reliable.