Decentralized Evaluation of Trust in Ad Hoc Networks using Neural Networks
Author
Abstract

Neural Network Security - Trust is an essential concept in ad hoc network security. Creating and maintaining trusted relationships between nodes is a challenging task. This paper proposes a decentralized method for evaluating trust in ad hoc networks. The method uses neural networks and local information to predict the trust of neighboring nodes. The method was compared with the original centralized version, showing that even without global information knowledge, the method has, on average, 97\% accuracy in classification and 94\% in regression problem. An important contribution of this paper is overcoming the main limitation of the original method, which is the centralized evaluation of trust. Moreover, the decentralized method output is a perfect fit to use as an input to enhance routing in ad hoc networks.

Year of Publication
2022
Date Published
oct
Publisher
IEEE
Conference Location
Thessaloniki, Greece
ISBN Number
978-1-66546-975-3
URL
https://ieeexplore.ieee.org/document/9941360/
DOI
10.1109/WiMob55322.2022.9941360
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