Intrusion Detection Based On Fuzzy C-means Algorithm

With the rapid development of network technology and the expansion of the scope of network applications,attacks and destruction to network will continue to increase.Network and information security is becoming the key issue for the further development of the Internet and network services and applications to be resolved.Intrusion detection technology is the new generation of security technology following the "firewall","data encryption" and other traditional security policies,which can identify malicious intention and act for computer and make the appropriate response. In recent years,intrusion detection is developing rapidly and playing an increasingly important role in the field of network and information security.This article discusses the classification of intrusion detection technology, commonly uses detection methods and principles,and analyzes the major issues and trends of the current intrusion detection systems(IDS). Traditional intrusion detection technology has many deficiencies,and advanced detection algorithm is the key technology for intrusion detection.This paper applies the artificial immune network algorithm and improved fuzzy c means(FCM) algorithm into the IDS.The algorithm is a typical unsupervised learning technique,and it is able to use the data that are not marked to generate IDS classifier, and it has the ability to detect new and unknown attacks.The researches include:(1)The FCM clustering algorithm needs people to input the clustering number C and it is sensitive to the initial value,in order to solve the deficiencies,the artificial immune network algorithm is introduced;(2)The paper improved FCM algorithm to make up for the defect of FCM algorithm which can only deal with numerical attributes;(3)The paper designs and implements intrusion detection system based on artificial immune network and fuzzy C means clustering algorithm,using KDD CUP99 data set to simulate the algorithm.Experimental results show that the algorithm has a higher detection rate and low false alarm rate,and has a good detection capability for unknown attacks.