Interactive decision-making method based on key historical behaviors in cloud computing environment

Abstract

The invention discloses an interactive decision-making method based on key historical behaviors in a cloud computing environment. The method includes a basic idea that, before the interaction between a cloud and an entity, both interactive entities respectively send a trust query request to a trust authentication center; the trust authentication center computes the overall trust degrees according to the key historical behavior of the user entity and the service entity, and issues trusts notes to the interactive entities based on the overall trust degrees; both entities perform interactive decision-making according to the trust notes. In the overall trust degree computing process, the trust of the entity is divided into direct trust and indirect trust, and the key historical behaviors are subdivided into a plurality of evaluation indexes by using a granular approach. The method can evaluate trust according to the key historical behaviors of the entities, and the data maintenance and evaluation processes are both executed at the trust authentication center, so that the method is a lightweight class interactive decision-making method. A key historical behavior window is set for trust evaluation, so that the interactive result is more accurate and meanwhile cumulative cheating is also avoided.

Description

technical field [0001] The present invention relates to an interactive decision-making method based on key historical behaviors in a cloud computing environment. The key historical behavior of the entity calculates its global trust degree, and on this basis, a trust ticket is issued for the interacting entity, and the two entities make interactive decisions based on the trust ticket. Among them, in the calculation process of the global trust degree, the trust of entities is divided into direct trust and indirect trust, and a fine-grained method is used to subdivide key historical behaviors into several evaluation indicators. It belongs to the field of computer network. Background technique [0002] With the development of high-speed Internet and mobile Internet, the network access capabilities of PCs and mobile terminals have been greatly improved, so that they do not have to be limited by their own computing resources. In addition, with the gradual maturity of virtualizat...

AI Technical Summary

Problems solved by technology

[0003] However, in the current research on trust-based interactive decision-making methods, the existing methods have the following deficiencies when making interactive decision-making: 1) Subjective evaluation methods such as expert opinions or average weighting methods are used for global trust evaluation, resulting in the results of interactive decision-making. There is greater subjectivity, which affects the scientific nature of credible decision-making

2) Only a few objective indicators such as success and satisfaction are used to measure the historical behavior of the entity. These coarse-grained methods cannot fully describe the key historical behavior attributes of the entity, so they cannot accurately predict the interaction results

3) The interaction history information is transmitted throughout the system through broadcasting, resulting in slow convergence in a large-scale distributed environment

4) The entity itself needs to evaluate the trust, increasing the burden on the entity, not a lightweight interactive decision-making method

[0004] Although the current research methods promote the research of trust relationship measurement and interactive decision-making methods, the above problems have not been solved, so new solutions are urgently needed

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