Abstract:
In the SloT (Social Internet of Things), trust determines whether the trustor (service requester (SR) or Service Consumer (SC)) will entrust the trustee (Service Provider (SP)) with specific services. Trust is key in SIoT. The main contribution is the design concept of a bidirectional, bi-stage, parameterized feedback-based, service-driven, attack-resistant trust and reputation system for the SloT, complete with a penalty technique for untruthful SPs and SRs, which reduces trust-related issues that arise during service provision and acquisition and increases trust between SPs and SRs. Social trust and QoS are used to evaluate both local and global SP reputation. Two-phase parameter-dependent feedback is advised to regulate SR intentions and skills and promptly identify suspected SRs. Based on reputation scores, the model places SPs on the White, Grey, or Black List. SP status determines maximum service charge. Rates are higher for White List SPs. SPs from other lists are unlikely to be chosen. SP's feedback improves its credibility. Categorization of SPs into status lists (White List, Black List, and Grey List) protect against OOA, DA, OSA, and SBA (SBA). SPs must be ethical and provide all advertised services honestly to maintain their Tglobal (global trust values). SPs can approve or deny SRs. SRs on the Temporarily Banned list can only request the services they're not prohibited for, while those on the Permanently Banned list can't request any service. This technique resists BMA, BSA, and SPA/GMA. Testing shows the trust and reputation management system can detect and prevent fraudulent SRs. Dishonest SPs lose consumers, credibility, and revenue when placed in the Black List. This system monitors SPs and SRs continuously. The experiments validate service-based reputation-based performance-based SP status listings. The tests reveal that SPs must be honest and provide good service to stay on the White List. Dishonest or malevolent SPs routinely change status listings, according to experiments. White List SPs having the best chance of being chosen and charge the most. Constant monitoring, penalty mechanisms, and performance-based SP categorization prevent DA, OOA, OSA, and SBA, as the results demonstrate. A potentially malicious SP gets listed in the Grey List or Black List, loses its global trust rating (Tglobal), and suffers reputational damage. SRs are impervious to SPA/GMA, BSA, and BMA due to their performance-based categorization into Suspect, Temporarily Banned, and Permanently Banned lists. The suggested trust and reputation management system improves the benchmark Eigen Trust Model and other SloT trust management systems.