In this paper we present a novel Intrusion Detection System which uses a hybrid approach based on a pattern matching engine and a neural network functioning in parallel to improve the detection efficiency. The attacks that this module is able to detect will be presented, as well as the methods used. This approach is based on the Netpy traffic monitoring and analysis tool which we developed. To test this approach we built a module for Netpy for intrusion detection. Furthermore, we prove that this approach is efficient for intrusion detection and also superior to any of the two individual methods.