Abstract: Network security is of paramount importance in the present data communication environment. Network security is a critical problem because a single attack can inflict catastrophic damages to the computers and network systems. The various hackers and intruders can create multiple successful attempts to cause the crash of the networks and web services by unauthorized intrusion. New threats and associated solutions to detect and prevent these threats are emerging together with the secured system evolution. The best solution to solve this issue is Intrusion Detection Systems (IDS). The important function of Intrusion Detection System (IDS) is to secure the resources from threats. In this study, we have presented a brief study about characteristics of ad hoc network, how they are problematic in ad hoc network security, attacks in ad hoc network and a description of some existing intrusion detection system. We have also justified why multiple intrusion detection is much better for ad hoc network with comparative study of existing intrusion detections in ad hoc network. This research proposed a new approach called Multiple Intrusion detection systems where the anomaly dataset is measured by the Neighborhood Outlier Factor (NOF). Here, trained model consists of big datasets with distributed storage environment for improving the performance of the proposed Intrusion Detection system. The experimental results proved that the proposed system identifies the anomalies very effectively than any other approaches. The experimental results proved that the proposed system identifies the anomalies very effectively than any other approaches.