Anomaly Based Intrusion Detection System Using Neural Network

Intrusion detection system (or IDS) is an integral part of any Information and Communication Technology (or ICT) system. Building an efficient and reliable IDS that accurately detects an attempt to compromise the network using some known or unknown vulnerability in real time is still a huge challenge. We attempt to create a state-of-the-art Deep Neural Network that analyses the network traffic in real time, identifies an attempt to compromise a network, classifies the type of attack and then compare its accuracy and efficiency with that of conservative and existing models.