Research on the Trust Mechanism of Individual Consumers in Rural Financial Markets Based on the Dynamic CGE Model

In order to obtain the complete equilibrium state of rural financial market and ensure the stable development of rural financial consumer market, this paper introduces CGE model and analyzes the dynamic trust mechanism of individual consumers in rural financial market. In this paper, the single variable evolutionary fuzzy clustering algorithm is used to analyze the orthogonal eigenvector solutions of individual consumers; the big data of individual consumers under the mode of perceived trust is automatically clustered, so as to obtain the fuzzy analogy function of individual consumers in the rural financial market; and finally the prediction value of consumer trust is obtained. The results show that trust, customer satisfaction, and service quality are positively correlated. Under the same sample expectation constraints, the dynamic CGE model is more robust, and the individual consumer trust mechanism of rural financial market in the study area has higher advantages.

T-RBAC Model Based on Two-Dimensional Dynamic Trust Evaluation under Medical Big Data

The professionalism and complexity of medical big data and the expensiveness of acquiring medical knowledge make it difficult for policymakers to judge whether the information accessed by doctors is necessary from a professional perspective and to formulate accurate access control strategies. To solve the above problems, this paper proposes a T-RBAC (trust-role based access control) model based on two-dimensional dynamic trust assessment, Using AHP and Grey theory to quantify the role attribute trust in the dimension of the doctor’s own attributes, Using Euler’s measurement method and probability statistics to quantify doctors’ behavioral trust in the dimension of historical behavior, then, the trust rule base performs hierarchical authorization based on the comprehensive trust value obtained by the weighted average. Multiattribute trust comprehensive evaluation makes the access control model have finer access granularity and higher security. At the same time, the introduction of time decay function and penalty function enhances the model’s sensitivity, dynamics, and resistance to bleaching attacks.

Dynamic-IoTrust: A Dynamic Access Control for IoT Based on Smart Contracts

The Internet of things (IoT) is an active, real-world area in need of more investigation. One of the top weaknesses in security challenges that IoTs face, the centralized access control server, which can be a single point of failure. In this paper, Dynamic-IoTrust, a decentralized access control smart contract based aims to overcome distrusted, dynamic, trust and authentication issues for access control in IoT. It also integrates dynamic trust value to evaluate users based on behavior. In particular, the Dynamic-IoTrust contains multiple Main Smart Contract, one Register Contract, and one Judging Contract to achieve efficient distributed access control management. Dynamic-IoTrust provides both static access rights by allowing predefined access control policies and also provides dynamic access rights by checking the trust value and the behavior of the user. The system also provides to detected user misbehavior and make a decision for user trust value and penalty. There are several levels of trusted users to access the IoTs device. Finally, the case study demonstrates the feasibility of the Dynamic-IoTrust model to offer a dynamic decentralized access control system with trust value attribute to evaluate the internal user used IoTs devices.

Enhancement of Reputation Aggregation based Dynamic Trust Protocols for Edge Computing based E-Health Care System

In recent years, E-services such as e-healthcare, e-learning, e-ticketing, depend on computer networks where the attackers have started introducing new types of attacks. Therefore, it is necessary to enhance security for communication which is needed for the transfer of confidential information relating to patients through the network. In our research we have developed a reputation aggregation based dynamic trust model for edge computing based E-health care systems. In this model, the edge node evaluates the trust value of a user and allows the user to access the E-health care system only when the trust value is satisfied. In order to do this, initially the user information is collected with the help of user agents and then this information is processed and the relevant data alone is sent to the edge nodes for evaluating the trust. Finally, the trusted users can be identified through edge nodes and they are only given the permission to access the e-health care system. Attacks generated in the simulations are detected using the prevailing algorithms and also the suggested techniques. The simulation results of this work prove the ability of the proposed techniques which are used to detect the attacks accurately and to prevent them effectively.