An Effective Credit Evaluation Mechanism with Softmax Regression and Blockchain in Power IoT

【Author】 Li, Da; Wang, Dong; Jiang, Wei; Guo, Qinglei; Bai, Desheng; Shi, Wei; Ruan, Linna

【Source】SECURITY AND COMMUNICATION NETWORKS

【影响因子】1.968

【Abstract】This paper is oriented to the credit investigation scenario of power grid supply chain enterprises and proposes a blockchain user credit assessment method based on improved Softmax regression in Power IoT. This method first designs a credit-rating mechanism that meets industry characteristics based on business needs. Second, it proposes a user credit evaluation model based on the blockchain architecture. Finally, the improved Softmax regression algorithm is used to train the proposed credit evaluation model, which effectively solves the credit rating. The multiclassification problem has achieved the goal of categorizing the credit rating of the enterprise. The simulation results show that the credit evaluation mechanism proposed in this paper can accurately evaluate the multisource credit data that lacks trust foundation and effectively realize the credit rating of power grid material supply chain enterprises. The credit evaluation mechanism proposed for Power IoT in this paper could have high potential for entity identity authentication and rating for securing mobile video communications.

【Keywords】

【发表时间】2022 14-Feb

【收录时间】2022-04-27

【文献类型】实证性文章

【主题类别】

区块链应用-实体经济-能源领域