Research On Intrusion Detection Based On Clustering Analysis

With great developments and extensive applications of technology of computer networks, especially for worldwide spread of internet, technology of computer and internet are continuously innovated and upgraded. Infrastructure and resource of computer networks have become increasingly important to nations, enterprises and individuals, ceaselessly change traditional way in which people live,work and study, and bring about new problems and challenges at the same time. With the increase of informatization level and enhancement of dependence on computer networks for human society, how to keep informatization society running normally,safely and steadily is the most important issue of which computer network safety is one to be always strengthened and improved. At present, application of interconnected network is extensively extended and its open characteristic is extensively strengthened,which causes more and more network systems exposed to threat of attacks and intrusions.Based on the research background stated above, this dissertation is to intend to develop research on network intrusion detection based on clustering method. In order to enhance the effectiveness for unknown intrusions, some network detection algorithms mainly using clustering analysis are proposed which are measured by the detection rate and the false positive rate, and are provided with computer simulations. Meanwhile, a scale-based clustering method is proposed, and apply it into the intrusion detection.The method has the ability to detect known and unknown intrusion from unlabeled intertnet connect record.