Blockchain-Based Trust and Reputation Management in SIoT

Abstract

In the Social Internet of Things (SIoT), trust refers to the decision-making process used by the trustor (Service Requesters (SRs) or Service Consumers (SCs)) to decide whether or not to entrust the trustee (Service Providers (SPs)) with specific services. Trust is the key factor in SIoT domain. The designing of a two-way, two-stage parameterized feedback-based, service-driven, attacks-resistant trust and reputation system for SIoT accompanied by a penalty mechanism for dishonest SPs and SRs is our main contribution that mitigates the trust-related issues occurring during service provisioning and service acquisition amongst various entities (SPs or SRs) and enhances trust amongst them. Our proposed methodology examines a SP’s local trust, global trust, and reputation by taking into account “Social Trust” and “Quality of Service (QoS)” factors”. Two—Stage Parameterized feedback” is incorporated in our proposed strategy to better manage “intention” and “ability” of SRs and provides early identification of suspicious SRs. This feature compels SRs to act honestly and rate the corresponding SPs in a more accurate way. Our recommended paradigm sorts SPs into three SP status lists (White List, Grey List, and Black List) based on reputation values where each list has a threshold with respect to the maximum service fee that can be charged. SPs in White List charge the most per service. SPs in other lists have a lower selection probability. Every feedback updates the SP’s trust and reputation value. Sorting SPs increases resistance against On Off Attack, Discriminatory Attack, Opportunistic Service Attack, and Selective Behavior Attacks. SPs must operate honestly and offer the complete scope of stated services since their reputation value relies on all their global trust values (Tglobal) for various services. Service requests may be accepted or denied by SPs. “Temporarily banned” SRs can only request unblocked services. SRs lose all privileges once on a “permanently banned” list. If local and global trust values differ by more than the threshold, the SR is banned. Our method also provides resistance against Bad Mouthing Attack, Ballot Stuffing Attack. Good Mouthing Attack/Self—Propagating Attack. Experiments indicate our trust and reputation management system recognizes and bans fraudulent SRs. “Dishonest SPs” are “blacklisted,” which affects their reputation, trust, and service charges.