By increasing use of computer network and internet using Intrusion Detection System (IDS) has become more popular. The main drawback of IDS is to generate alert to system administrator based on malicious activities that violates security policies. Recently fuzzy logic plays a vital role in detecting attacks using various rule generation technique. This paper proposed a new concept of using various fuzzy rule generation to detect intrusion in an effective manner. The experimental analysis are done on NSL-KDD intrusion detection dataset, it's clear that the proposed system achieve high detection rate and reduce false alarm rate than other existing machine learning algorithm such as neural network, data mining and many more which are used to identify whether record is normal or attack .