This paper aims at creating a new Trust Management System (TMS) for a system of nodes. Various systems already exist which only use a simple function to calculate the trust value of a node. In the age of artificial intelligence the need for learning ability in an Internet of Things (IoT) system arises. Malicious nodes are a recurring issue and there still has not been a fully effective way to detect them beforehand. In IoT systems, a malicious node is detected after a transaction has occurred with the node. To this end, this paper explores how Artificial Intelligence (AI), and specifically Linear Regression (LR), could be utilised to predict a malicious node in order to minimise the damage in the IoT ecosystem. Moreover, the paper compares Linear regression over other AI-based TMS, showing the efficiency and efficacy of the method to predict and identify a malicious node.
CITATION STYLE
Subramanian, A. K., Samanta, A., Manickam, S., Kumar, A., Shiaeles, S., & Mahendran, A. (2021). Linear Regression Trust Management System for IoT Systems. Cybernetics and Information Technologies, 21(4), 15–27. https://doi.org/10.2478/cait-2021-0040
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