Dynamic Trust Evaluation Research Articles

ACO-BTM: A Behavior Trust Model in Cloud Computing Environment

AbstractConsidering trust issues in cloud computing, we analyze the feasibility of adopting ant colony optimization algorithm to simulate trust relationships between entities in the cloud and then propose a novel behavior trust model: ACO-BTM. Trust relationships between entities in cloud computing are dynamic, uncertain and hard to quantify. ACO-BTM introduces the conception of ‘pheromone’ and transition probability to represent behavior trust. Then, it focuses on the research of dynamic trust evaluation, time constraint and some other issues. Furthermore, a detailed algorithm process of behavior trust evaluation is given in this context. Finally, ACO-BTM is applied to cloud computing platform to simulate the establishment of behavior trust relationships. The simulation experiment verifies that trust degree change with time varies and the frequency of interactions. Compared with the other model, ACO-BTM can provide better trust recommendation services and protect against attacks of malicious nodes effect...

A Dynamic Trust Evaluation Model for Internet Computing

Trust mechanism has been identified as one of key areas in the field of Internet security. Our objective in this paper is to develop a dynamic trust evaluation model for Internet computing. The proposed scheme divides the recommendation trust into the direct recommendation trust and the indirect recommendation trust, and considers variety of factors to calculate the two types of recommendation trust degree. Simulation results show that, compared to the existing trust model, the model can effectively improve the accuracy of trust evaluation, and provide a better capacity of resisting malicious entities.

A New Approach of Trust Relationship Measurement Based on Graph Theory

The certainty trust relationship of network node behavior has been presented based on graph theory, and a measurement method of trusted-degree is proposed. Because of the uncertainty of trust relationship, this paper has put forward the random trusted-order and firstly introduces the construction of trust relations space (TRS) based on trusted order. Based on all those above, the paper describes new method and strategy which monitor and measure the node behavior on the expectancy behavior character for trusted compute of the node. According to manifestation of node behavior and historical information, adjust and predict the trusted-order of node behavior. The paper finally establishes dynamic trust evaluation model based node behavior characters, and then it discusses the trusted measurement method which measures the connection and hyperlink for node behavior of network in trust relationship space.

Dynamic trust evaluation and scheduling framework for cloud computing

Cloud computing has become a scalable services consumption and delivery platform in the field of computer science. As more and more consumers delegate their tasks to cloud providers, service level agreements (SLAs) between consumers and providers emerge as a key aspect. Because of the dynamic nature of the cloud, continuous monitoring on quality-of-service attributes is necessary to enforce SLAs. In this paper, we propose a trust mechanism-based task scheduling model for cloud computing. Referring to the trust relationship models of social persons, trust relationship is built among computing nodes, and the trustworthiness of nodes is evaluated by utilizing the Bayesian cognitive method. Integrating the trustworthiness of nodes into a dynamic level scheduling algorithm, the trust dynamic level scheduling algorithm for cloud computing is proposed. Theoretical analysis and simulations prove that the proposed algorithm can efficiently meet the requirement of cloud computing workloads in trust, sacrificing fewer time costs, and assuring the execution of tasks in a secure way in cloud environment. Copyright © 2011 John Wiley & Sons, Ltd. (A trust mechanism based task scheduling model for cloud computing is provided. Trust relationship is built among computing nodes by utilizing the Bayesian cognitive method. The trust dynamic level scheduling algorithm can efficiently meet the requirement of cloud computing workloads in trust and assuring the execution of tasks in a secure way.)

A Trust Model Based on Cloud Model and Bayesian Networks

the Internet has been becoming the most important infrastructure for distributed applications which are composed of online services. In such open and dynamic environment, service selection becomes a challenge. The approaches based on subjective trust models are more adaptive and efficient than traditional binary logic based approaches. Most well known trust models use probability or fuzzy set theory to hold randomness or fuzziness respectively. Only cloud model based models consider both aspects of uncertainty. Although cloud model is ideal for representing trust degrees, it is not efficient for context aware trust evaluation and dynamic updates. By contrast, Bayesian network as an uncertain reasoning tool is more efficient for dynamic trust evaluation. An uncertain trust model that combines cloud model and Bayesian network is proposed in this paper.