IoT Intrusion: Detection Methods and Mitigation Strategies

In the age of revolutionized concepts of smart homes, offices, cities, industries, vehicles, the Internet of Things (IoT) devices play an integral role in collecting data, network for communication and cloud for processing and storage. Each of these layers of IoT are vulnerable to attacks, predominantly due to the leverages IoT requires in terms of storage, processing. Hence, there arises demand to secure IoT by detecting the intrusion in time and formulate mitigation to safeguard the devices and protect the data be it personal or commercial. This study presents IoT Intrusion Detection Methods like Machine Learning (ML) and Deep Learning (DL) methods at varying accuracies and mitigation strategies to bypass attacks and safeguard the network as well as devices within the network. This study summarizes various approaches in place for both detection and mitigation that can form the basis for future studies.