Abstract:- Asystem Network intrusion discovery framework (NIDS) helps the system admin toidentify network security breaks in their own association.Nonetheless, numerousdifficulties emerge while building up an intelligent and effective NIDS forunexpected and capricious attacks. In recent years, one of the foremost focusesinside NIDS studies has been the application of machine learning knowledge oftechniques. Proposed work present a novel deep learning model to enable NIDSoperation within modern networks. The model shows a combination of deeplearning, capable of correctly analyzing a wide-range of network traffic.Moreover, additionally proposes novel deep learning classification displaybuilt utilizing feature extraction techniques. The performance evaluatednetwork intrusion detection analysis dataset, particularly KDDCUP dataset.
Keywords– Deep andMachine Learning, Intrusion Detection, Auto-Encoders, KDD, Network Security.