Algorithms Of Intrusion Detection Based On Intelligent Computation

With the development of network technology and with the growing usage of network, the number of attacks is increasing. As attacks on computer systems are becoming increasingly multiplex, sophisticated and intelligent, it is very difficult to keep systems safe only by static safeguards such as firewall. As active defense technology, IDS (Intrusion Detection System) compensates the defects of traditional defense technology, but in the face of rapid updated network configurations, the drastic increase of network traffic and so many new attack methods, traditional IDS has some limitations. So how to prevent computer and network from a variety of attacks in progress becomes an important problem to be solved.Based on the background stated above, this dissertation is to intend to develop research on intrusion detection based on intelligent Computation. In order to enhance the effectiveness for unknown intrusions, some intrusion detection algorithms are proposed and are proved with computer simulations in this paper.The innovations of this paper are:I. We present the algorithm of Minimax Probability Machine classifier. A new multi-layer classifier model based on MPM ensemble with boosting is proposed and is applied to intrusion detection in this paper.II. The Support Vector Machine is a stable algorithm and has better generalization ability.To obtains the key feature we apply Immunodominance Clone Algorithms to optimize the training data in the intrusion detection system. Utilizing multi-layer classifier model based on SVM ensemble with boosting in optimized data, the generalizing ability of IDS is still good when the training time is small.III. A novel classification method, Organizational CoEvolutionary algorithm for Classification (OCEC), is proposed by Liu Jing et., which is different from the GA-Based classification methods available. The evolutionary operations of OCEC do not act on rules, but on the given data directly, and rules are extracted from the final evolutionary results, which can avoid generating meaningless rules during evolutionary process.In this paper we take into account the feature of the intrusion dataset and introduce the fuzzy logic into Organization CoEvolutionary algorithm and give an intrusion detection models based on Organization CoEvolutionary Fuzzy Classification.We simulate the methods presented in this paper with the kddcup99 dataset and get a satisfied result. It indicates that the new method is feasible and effective.