  Network security is a growing issue, with the evolution of computer systems
and expansion of attacks. Biological systems have been inspiring scientists and
designs for new adaptive solutions, such as genetic algorithms. In this paper,
we present an approach that uses the genetic algorithm to generate anomaly net-
work intrusion detectors. In this paper, an algorithm propose use a
discretization method for the continuous features selected for the intrusion
detection, to create some homogeneity between values, which have different data
types. Then,the intrusion detection system is tested against the NSL-KDD data
set using different distance methods. A comparison is held amongst the results,
and it is shown by the end that this proposed approach has good results, and
recommendations is given for future experiments.
