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DEIT: Dempster Shafer Theory‐based edge‐centric Internet of Things‐specific trust model
Author(s) -
Bhargava Arpita,
Verma Shekhar
Publication year - 2021
Publication title -
transactions on emerging telecommunications technologies
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.366
H-Index - 47
ISSN - 2161-3915
DOI - 10.1002/ett.4248
Subject(s) - computer science , variable (mathematics) , enhanced data rates for gsm evolution , computer security , identification (biology) , edge computing , edge device , credibility , value (mathematics) , the internet , trust anchor , internet of things , computational trust , artificial intelligence , machine learning , cloud computing , world wide web , mathematics , reputation , biology , mathematical analysis , botany , political science , law , operating system , social science , sociology
The potential benefits of edge‐centric Internet of Things (IoT) come with increased security threats and because the edge devices may be compromised into sending or forwarding wrong information. To negate the effect of wrong information on inference, such messages need to be identified. Identification and dropping of messages in the network as early as possible would minimize the communication overhead. Trust values of nodes help in the early identification of such messages. In this work, the Dempster Shafer Theory (DST)‐based edge‐centric IoT‐specific Trust Model (DEIT) is designed to compute trust to include the specific characteristics of IoT. Edge servers use DEIT to compute trust value of edge devices in the network. In DEIT, DST combines the available trust messages. DIET also uses the degradation variable, credibility variable, punishment variable, re‐compensating variable, and pardoning variable to compute final trust value. The computed trust value assists the edges in taking correct decisions. Simulation results demonstrate that it can immediately capture two major types of misbehavior, namely, information drop and modification under both sparse and dense traffic conditions. Through scenarios in the results section, the depiction of various possible misbehaviors has been discussed. Scenario 1 and 2 discuss a situation where a malicious edge device misbehaves in two ways, namely, dropping and modification of information, respectively. In scenario 3 and 4, situations are discussed when the trust opinion of the trusted and distrusted devices are neutralized with time using the degradation factor to illustrate and compare changes in trust values in two different situation.