Research On Generation And Vulnerability About The Second Distribution Of Real Value Detector Based On Immune Mechanism

The rapid development of computer Internet and human social life have thegrowing demand for Internet. It makes network security occupy a key position inInternet and the further development of network services and applications.Biological immune system is a highly autonomous and distributed system. It hasa good natural feature in the architecture, the coordination mechanism and theaction capacity and so on. Intrusion detection system sets up a similar completearchitecture and disposed mechanism under its inspiration from a bionic point ofview. Furthermore, the artificial immune theory is established a intelligent bionictheory based on biology. This makes the intrusion detection system based on theimmune mechanism have an important value.In the intrusion detection system, the detection is the core component. Thispaper uses it as the research object. Firstly, it regards the detector generationmechanism as starting point and constructs an n-dimensional chaotic map withchaos theory. It makes use of good chaotic properties to optimize detectorgeneration mechanism. At the same time, the part of the traditional V-detectoralgorithm to determine the detector radius has been improved and it presents thereal value negative selection algorithm with the n-dimensional chaotic map. Thealgorithm not only reduces the individual redundancy with maintaining thediversity of the population, but also improves the generation speed of detectorseffectively.Secondly, for the loophole problem that is caused by the inherent reasons ofthe detector generation and the first distribution, this paper presents the realvalue detector generation algorithm based division and movement (RVGA_DM).It based on the omission data detected and does the secondary distribution in loopholes of non-self space through the method of division and movement.Studies show that the algorithm avoids the vulnerability production effectivel yand reduces the omission rate of the detection system.Finally, for two parameters r and r0in the RVGA_DM algorithm, it does theestimation analysis on the two parameters. On the one hand, it constructs theobjective function using them as independent variables from the perspective ofproblem solution. On the other hand, it combines chaos theory with clonalselection idea properly and puts forward the adjustive chaos clonal selectionalgorithm from the perspective of the analysis on problem solution. It not onlysolves the problem of the parameter setting and estimate, but also provides a newidea of the related problem about parameter estimate and theoretical support.