Trust management

Trust establishment (TE) among sensor nodes has become a vital requirement to improve security, reliability, and successful cooperation. Existing trust management approaches for large scale WSN are failed due to their low cooperation (i.e., dependability), higher communication and memory overheads (i.e., resource inefficient). This paper provides a new and comprehensive hybrid trust estimation approach for large scale WSN employing clustering to improve cooperation, trustworthiness, and security by detecting selfish sensor nodes with reduced resource (memory, power) consumption. The proposed scheme consists of unique features like authentication based data trust, scheduler based node trust, and attack resistant by giving the high penalty and minimum reward during node misbehavior. A task scheduling mechanism is employed for scheduling the significant task to reduce computation overhead. The proposed trust model would be capable to provide security against blackhole attack, grey hole attack, and badmouthing attack. Moreover, the proposed trust model feasibility has been tested with MATLAB. Simulation results exhibit the great performance of our proposed approach in terms of trust evaluation cost, prevention, and detection of malicious nodes with the help of analyzing consistency in trust values and communication overhead.

Today, the Internet of Things is a widely recognized phenomenon that generates a significant amount of data and connects many devices. Many products are incorporating electronic components to facilitate their integration and interaction with the Internet. Scalable and efficient trust management systems are required to maintain network reliability, considering the increasing number of IoT devices and generated data. In order to enable scalable trust management in social IoT, this paper presents a sharding-based scalable trust management approach that combines social interactions with smart contract functionality. Through the division of transaction state into smaller segments and the enhancement of trust value propagation among connected devices, sharding techniques in blockchain can offer scalable trust management protocols. When implementing the model on the Hyperledger Fabric platform, we carried out a thorough evaluation. The model calculates trust in terms of trust convergence and success rate efficiently. We have conducted several tests to evaluate the scalability of the model. To boost it, we have also implemented the state sharding. We also conducted a study to highlight the advantages of the sharding strategy on the scalability of the model. The results demonstrate that using shards significantly improves trust management capacity on the blockchain. The proposed method demonstrates the potential application of sharding in blockchain-based Trust Management (TM) for scalable trust management in SIoT.