Comparative Analysis of Machine Learning Algorithms for Securing IoT Enabled Environment
Amit Sagu, Nasib Singh Gill, Preeti Gulia, Deepti Rani, Ayushi Chahal · 2022 International Conference on Computing, Communication, and Intelligent Systems (ICCCIS) · 2022
The IoT (Internet of Things) link system, various applications, data storage like cloud, and another service area that possibly will be a fresh entry for attackers as they uninterruptedly offer services in the organization. At this time, threats to users’ privacy and malware pose significant challenges to the integrity of the Internet of Things. These extortions might lead to the loss of important information, which in turn could cause a company’s finances and reputation to suffer. In this paper, we have identified anomalous activity throughout the IoT ecosystem by utilizing a variety of machine learning approaches. The results from the experiment indicate that the categorization capabilities of machine learning techniques may serve as an alternative strategy for ensuring the safety of communication inside the IoT.