Research On Trust Evaluation Model Of Internet Of Things

In recent years,with the continuous development of technologies such as radio frequency identification,sensor networks and other areas,the Internet of Things(IoT)has been widely used in various fields such as medical,smart home,and has also shown broad application prospects.In IoT,large-scale smart devices cooperate in the network according to their specific needs.However,due to the openness of the IoT,service diversity,and limited node energy,the security of the IoT is facing severe challenges.Trust evaluation can predict the cooperation probability and service capability of a node before the node establishes cooperation,so that a part of the malicious node can be filtered before the node cooperation establish.Therefore,in IoT,a trust evaluation mechanism which can fully exploiting node trust relationships and effectively identifying malicious nodes is of great significance for safeguarding IoT security and service quality.Firstly,the main security issues the IoT facing were expounded,the significance of the trust evaluation model in safeguarding the IoT security was analyzed..And then the research status of the IoT trust evaluation model was summarized,and the advantages and disadvantages of the EngienTrust model and the RFSN framework were analyzed,which laid a foundation for the follow-up research.Secondly,an IoT node comprehensive trust evaluation model(INCTEM)was proposed.In INCTEM,the node's same quality service strength evaluation index was introduced to reduce the impact of non-intrusive factors on trust evaluation,as well as the dynamic trust attenuation factor was added to realize the calculation of dynamic trust value to eventually improve the Bayesian-based direct trust evaluation method.And the recommended node's reliability was evaluated from three aspects: node similarity,evaluation difference and trust value of the node itself,and then used as recommendation trust weight to suppress node malicious recommendation behavior.At the same time,a penalty or reward for malicious recommendation nodes through a feedback trust mechanism was adopted to Suppress malicious recommendation behavior.Finally,the adaptive weights of direct and recommended trust were calculated to compute the comprehensive trust value.Finally,the simulation experiments were conducted to verify the effectiveness of the model in characterizing the node's behavior,the ability to suppress malicious recommendation behavior and reduce transmission energy consumption.The simulation results show that,compared with other models,INCTEM has certain advantages in dealing with malicious services and malicious recommendation behaviors,and can reduce transmission energy consumption while ensuring accurate trust calculation.