The Reputation Model of Multi-Stage Dynamic Game

Aim To study the implicit restriction mechanism for hidden action in multi stage dynamic game. Methods A reputation model for restriction on repeated principal agent relationship was established by using the theory on principal agent problem in information economics and the method of game theory to study the implicit restriction mechanism for hidden action. Results and Conclusion It is proved that there exists implicit restriction mechanism for the multi stage principal agent relationship, some conditions for effective restriction are derived, the design methods of implicit restriction mechanism are presented.

RRM:An incentive reputation model for promoting good behaviors in distributed systems

Reputation systems represent soft security mechanisms that complement traditional information security mechanisms. They are now widely used in online e-commerce markets and communities in order to stimulate good behaviors as well as to restrain adverse behaviors. This paper analyzes the limitations of the conversational reputation models and proposes an incentive reputation model called the resilient reputation model （RRM） for the distributed reputation systems. The objective of this reputation model is not only to encourage the users to provide good services and, therefore, to maximize the probability of good transaction outcomes, but also to punish those adverse users who are trying to manipulate the application systems. The simulation results indicate that the proposed reputation model （RRM） could effectively resist against the common adverse behaviors, while protecting the profits of sincere users from being blemished by those adversaries.

Trusted GPSR protocol without reputation faking in VANET

In vehicular ad hoc network(VANET), misbehaviors of internal nodes, such as discarding packets, may lead to a rapid decline in packet delivery ratio. To solve this problem, an improvement of greedy perimeter stateless routing(GPSR) protocol is presented. In the new protocol, trustworthiness is considered in the route selection process. The trustworthiness is measured by an objective trust model based on the subjective trust model Dy Trust. And the reputation value which reflects the trustworthiness of each node is calculated and broadcasted by the intersection nodes. Specially, besides resisting the packet-discarding behavior of selfish nodes, this protocol also includes a location detection process to resist the location-faking behavior of malicious nodes. As a result, the selfish nodes and the malicious nodes can be excluded from the network. In addition, compared with improved GPSR protocol, the presented one is able to resist one kind of reputation-faking attack and has better performance in simulation.

A hierarchical byzantine fault tolerance consensus protocol for the Internet of Things

The inefficiency of Consensus protocols is a significant impediment to blockchain and IoT convergence development.To solve the problems like inefficiency and poor dynamics of the Practical Byzantine Fault Tolerance(PBFT)in IoT scenarios,a hierarchical consensus protocol called DCBFT is proposed.Above all,we propose an improved k-sums algorithm to build a two-level consensus cluster,achieving an hierarchical management for IoT devices.Next,A scalable two-level consensus protocol is proposed,which uses a multi-primary node mechanism to solve the single-point-of-failure problem.In addition,a data synchronization process is introduced to ensure the consistency of block data after view changes.Finally,A dynamic reputation evaluation model is introduced to update the nodes’reputation values and complete the rotation of consensus nodes at the end of each consensus round.The experimental results show that DCBFT has a more robust dynamic and higher consensus efficiency.Moreover,After running for some time,the performance of DCBFT shows some improvement.