Network Intrusion detection systems aim is detecting attacks against computer systems and networks.  This paper focuses on the development of Genetic Algorithm in Intrusion Detection System (GAIDS). Genetic Algorithms can provide appropriate heuristic search methods. However, balancing the need to detect all possible attacks found in network with the need to avoid false positives is a challenge, given the scalar fitness values required by Genetic Algorithms. This study discusses a fitness function independent of variable parameters to overcome this problem. This fitness function allows the IDS to significantly reduce both its false positive and false negative rate.