Author : Miss.Bhakti Nandurdikar and Prof.Rupesh Mahajan

A framework Network intrusion discovery framework (NIDS) helps the system admin to identify network security breaks in their own affiliation. Regardless, various troubles rise while developing a canny and powerful NIDS for unexpected and capricious attacks. In recent years, one of the preeminent focuses inside NIDS examines has been the application of machine learning knowledge of techniques. Proposed work present a novel deep learning model with support vector machine classifier to enable NIDS operation within modern networks. The model shows a combination of deep learning and machine learning, capable of correctly analyzing a wide-range of network traffic. This model increases the accuracy ,Precision and recall with reduced training time over existing system. Moreover, additionally proposes novel deep learning classification display built utilizing feature extraction techniques. The performance evaluated network intrusion detection analysis dataset, especially KDD CUP and NSL KDD dataset.

Keywords: Deep and machine learning, intrusion detection, Auto-encoders, Network security