Join of Fuzzy Genetic approaches for Intrusion Detection An Efficient Intrusion Detection System Based on Fuzzy Genetic approaches

One of the solutions for the security of the systems and computer networks is the formation of intrusion detection systems. In the design of these systems, the techniques of artificial intelligence such as neural network, data miningtechniques, expert systems, genetic algorithms and fuzzy systems are applied. The main aim is the design of thesystem that besides exact detection is with low error. The main aim of detection in these systems is their analyzer. Itseems that if the input of analyzer of the systems is language variables and final detection is done as fuzzy inference,the results of the analysis get better and an exact detection is done. In addition to reduction of error, it can present good information in the form of fuzzy rules to the security expert of the system. Genetic algorithms by flexible and prevalent searching ability can be applied for optimized learning of fuzzy system rule base. The current paper aimed to evaluate, design and implement fuzzy genetic intrusion detection system. The experiments and the results showed the considerable effect of using the proposed architecture on the improvement of detection. [Life Science Journal 2013;X(X): X-XX]. (ISSN: 1545-0740).

Keywords:

Intrusion Detection systems , Fuzzy Logic , Genetic Algorithm , Classification , Evolution Methods , Attack Production Tools