Ant Colony Mining Algorithm and Its Appliances in Intrusion Detection Systems

摘要：

Data mining technology has been introduced into intrusion detection systems because of its ability in dealing with mass data. It can dig out normal and intrusion behavior patterns from a large number of records and generate rules automatically, so its adaptability and scalability are strong. In this paper, classification techniques applied in intrusion detection systems are intensively discussed. Aiming to tackle the deficiencies of traditional classification algorithms, ant colony algorithm is introduced and a mining algorithm named Ant Colony Mining Algorithm (ACMA) is proposed as well. Experiments and simulations are conducted. The performance of ACMA is verified by the comparative experiments. Also, the feasibility of applying data mining to intrusion detection systems is strongly confirmed.

关键词： Ant Colony Mining Algorithm Classification Data Mining Ant Colony Algorithm Intrusion Detection Systems

作者: SUN Li-juan GUO Jian XIAO Fu WANG Ru-chuan

作者单位: School of Computer, Nanjing University of Posts and Telecommunications Nanjing University of Posts and Telecommunications Nanjing, China

会议类型: 国际会议

会议名称: 2010 International Conference on Measurement and Control Engineering(2010年IEEE测量与控制工程国际会议 ICMCE2010)

会议地点: 成都

会议语种:英文

页码: 709-713

在线出版日期: 2010-11-16（万方平台首次上网日期，不代表论文的发表时间）