Study of Integration and Simulation of Various Intrusion Detection Techniques

In security infrastructure network intrusion detection system plays an important role. There are number of novels attacks in present scenario and it is not an easy to determine that. So in this paper we discuss the few new integrated network detection system. This paper also gives a better NIDS as a result because the numbers of good techniques have been integrated in this paper. So as conclude number research problem can be answered by this study. This article further can be a outline or can be a road map for researchers as it will provide answers about the problems and further research in the existing system. Keywords: Intrusion Detection System, NIDS, Data Mining, Fuzzy Agent based Intrusion Detection. 1. Intrusion Detection Using Data Mining Along Fuzzy Logic and Genetic Algorithms Based on fuzzy set theory, fuzzy logic provides a powerful way to categorize a concept in an abstract way by introducing vagueness. On the other hand, data mining methods are capable of extracting patterns automatically from a large amount of data. The integration of fuzzy logic with data mining methods will help to create more abstract patterns at a higher level than at the data level. Decreasing the dependency on data will be helpful for patterns used in intrusion detection. Munish Gupta, Manish Saxena, Prof. D.B.Singh, Prof. Rizwan Beg, The International Journal of Computer Science & Applications (TIJCSA) ISSN – 2278-­‐1080, Vol. 1 No. 12 February 2013