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Artificial Immune Detector Matching Rules

Posted on:2009-07-12Degree:MasterType:Thesis
Country:ChinaCandidate:Y ZhuFull Text:PDF
GTID:2208360245461427Subject:Computational Mathematics
Abstract/Summary:PDF Full Text Request
Along with the Internet rapid growth, the network has presently influenced the society on politics, economics, culture, military and social life etc. Meantime,the network security has become the focus of every country. For the time being, Internet security technology includes intrusion detection technology, fire wall, security routers and so on. Because intrusion detection system (IDSs) have relatively better identifying ability against various sorts of intrusions , IDS turns to be a main part of the P2DR (police, protection, detection, response) security model.From Anderson's intrusion detection conception model in 1980s, although intrusion detection technology has made great progress, it still has some defects and disadvantages such as low detection rate for novel attacks, high frequency of false alarm, etc. To solve these difficult problems in intrusion detection, this dissertation focuses on the feature extraction, matching algorithm and building of detector model based on intrusion detection and makes some preliminary progresses in the following aspects:1.Principle Component Analysis (PCA) are studied. 41 bits data are compressed 7 bits data. Amounts of experiments for intrusion detection with the KDDCUP99 dataset are conducted, and the results show that the data dimension using PCA is reduced obviously, the speed of detection is quickened and level of detection is not changed obviously and that pressing these data is practicable.2.A matching algorithm is improved. I put forward an advanced Multi-pattern matching algorithm based on BM algorithm and Multi-pattern matching algorithm. Large amount of experiments for the advanced Multi-pattern are conducted, and the result of the experiment demonstrate that the speed of matching is quickened obviously.3.At building of detector, I improve model of negative detection .And this improved model of detector applicant Principle Component Analysis and advanced Multi-pattern matching algorithm. A t last, this model of detector is practicable through a experiment.
Keywords/Search Tags:intrusion detection, artificial immune system, Principle Component Analysis, matching algorithm, detector model
PDF Full Text Request
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