Intrusion Detection Systems (IDSs) are used to find the security violations in computer networks. Usually IDSs produce a vast number of alarms that include a large percentage of false alarms. One of the main reason for such false alarm generation is that, in most cases IDSs are run with default set of signatures. In this paper, a scheme for network specific false alarm reduction in IDS is proposed. A threat profile of the network is created and IDS generated alarms are correlated using neural network. Experiments conducted in a test bed have successfully filtered out most of the false alarms for a range of attacks yet maintaining the Detection Rate. Copyright © 2010 John Wiley & Sons, Ltd.