Abstract-Now a days, with the growing use of the computers, a consistent case of the vulnerabilities is also increased frequently. To improve the security of computer system various approaches have been proposed from different areas. One such approach is make a use of AIS in Intrusion Detection System. The threats and intrusions in computer network have similarities with human diseases, therefore IDS basically can be compared to biologic immune system. In this case human body deals with an effective approach namely HIS (Human Immune System) which affords a high level security to human body from the invasion of pathogens and can be utilized for the identification and protection of unnoticed intruders. To enhance the efficacy of IDS, AIS (Artificial Immune System) can play a vital role, which provides influential features in the design of IDS. This paper gives a new way to the anomaly detection problem. To detect the anomaly problems and unnoticed intruders, negative selection algorithm method is found more suitable than K-Mean Clustering method.