Recent trend in Intrusion detection using Fuzzy-Genetic algorithm

Abstract: Computer networks have expanded significantly in use and this makes them more vulnerable to attacks. It is really important to secure the data from any intrusive attacks so intrusion detection is really very helpful in the field of computer network security. Intrusion detection is the act of detecting unwanted traffic on a network. Many current intrusion detection systems are unable to find unknown attacks. A no. of GA and fuzzy logic based approaches are used for detecting network intrusions. This paper presents a survey of these approaches in intrusion detection with advantages. KDD cup data used in every technique which have information of computer networks during normal and intrusive behavior. It contains basically four categories of attacks. GA is used to optimization purpose and fuzzy logic work on approximation rather than precise values. NSLKDD is an advance version of KDD cup data set.

Keywords: Anomaly detection, Fitness function, Nsl Kdd, Network attacks