Systematic Analysis of Tools Employed in Threats Detection in Iot Environment
P. Pavithra, P. Durgadevi · 2022 International Conference on Advances in Computing, Communication and Applied Informatics (ACCAI) · 2022
The Internet of Things (IoT) is a network of interconnected devices that can transmit data over a network without the need for physical interactions. IoT devices include wearable sensors, software, actuators, and computer devices. They are linked to a specific object that connects through the internet. At the same time, the lack of protection for IoT devices has increase in security threats. IoT attacks are one of the most common illegal activities involving in IoT, they spread quickly and can cause so much more harm than other destructive activities. In recent years, the Intrusion Detection System has shown to be a helpful tool for securing data in IoT devices. This study presents an Intrusion Detection System (IDS) based on machine learning that can detect and mitigate security threats in an IoT context. The paper hence, carried out a comparative review of literature on previous researches and studies on attack identification using Machine language techniques. Machine approach are the most appropriate detective control approach against threats generated from IoT devices. The goal of this work is to provide a comprehensive survey of ML methods that can be used to develop improved security methods IoT devices.