DDoS Intrusion Detection System Based on Data Mining
Changchun Yang, NI Tong-guang, Xue Heng-xin · Jisuanji gongcheng · 2007
Defending distributed denial of service(DDoS) attacks is one of the most difficult security problems in Internet.A novel intrusion detection system based on data mining to detect DDoS attacks in real time is presented.K-means cluster algorithm combining Apriori association algorithm is used to group the quantitative attributes in network traffic,and extracts traffic patterns from network data to generate detection models.Experimental result shows that DDoS attacks can be detected efficiently.