NETWORK INTRUSION DETECTION SYSTEM USING MACHINE LEARNING

Abstract—home and network intrusion detection system (HNIDS) is an intriguing problem that is being addressed in more recent research studies.this review is focused on recognizing intrusion in homes and computer networks based on image and numerical datasets respectively.diverse approaches have been tried over the past years.profuse methods are offered to acknowledge varied types of attacks such as botnet,DoS,DDos with respect to networks and breaking and entering,jumping a wall as actions in home intrusion to list a few. For each methodology,multiple algorithms and datasets are used.data is obtained in several ways such as cctv footage, images,sensors,computer logs,attack signatures.the expected outcomes by each approach and dataset are then compared.

Keywords: home and network intrusion detection system,HNIDS,ML,GAN,LSTM