Survey on Intrusions Detection System using Deep learning in IoT Environment
Raja Rajeswari Balaji, S. Deepajothi, G Prabaharan, T. Daniya, P. Karthikeyan, S. Velliangiri
Abstract
The enormous development of information sent through the IoT devices to end-user devices has expanded the significance of creating intrusion detection systems. Intrusion detection system plays a vital role in the smart home, smart city, agriculture, and business organizations. The intruder crate attack and send the data through the IoT sensor device to attack the IoT environment. There is numerous deep learning model is developed and deployed in the IoT environment to detect the intrusion's activity in the IoT environment. This survey paper explores the deep supervised learning model, deep unsupervised learning model, and data set used in the IoT environment for the intrusions detection system. Finally, the open research problem in the intrusion detection system in the IoT environment is presented.