Credibility measuring method combining Bayesian algorithm and MapReduce

Abstract

The invention relates to a credibility measuring method combining a Bayesian algorithm and a MapReduce. The credibility measuring method combining the Bayesian algorithm and the MapReduce comprises the following steps that S01, a Bayesian filter algorithm is used for carrying out credibility evaluation on behavior records generated in the process of mobile terminal interaction, statistics is carried out on the prior probability of training data centralization, the posterior probability of the behavior records is calculated through a Bayes formula, and the maximum posterior probability is selected to serve as the credibility of the behavior records; S02, probability distribution evaluation is carried out on credible records through a Bayesian inference algorithm with a Dirichlet process, and prediction of the credibility of mobile terminals can be obtained; S03, selection of a characteristic value is achieved through an information gain algorithm. The credibility measuring method combining the Bayesian algorithm and the MapReduce achieves high efficiency, safety and neutrality in the process of calculation and storage of the credibility with the help of a cloud computing platform, and safe storage and high-performance calculation of data are ensured.

Description

technical field [0001] The invention relates to a trust measurement method combining Bayesian algorithm and MapReduce. Background technique [0002] The existing network trust model provides a reference theoretical basis for the research on communication trust between mobile terminals, and is mainly divided into two categories: centralized trust measurement and distributed trust measurement. Distributed trust measurement starts from a subjective point of view and combines the concept of trust to judge the behavior attributes, behavior interactions and results of nodes, and realizes the subjective and credible evaluation of node behavior to a certain extent. At present, research in this field has achieved some important results, among which the more influential works include: EigenTrust, PowerTrust, PeerTrust, R2BTM, DRS (Dirichlet Reputation Systems), FTE (Fuzzy-based Trust Evaluation), PRMGST, etc. Among them, DRS considers that the trust evaluation of nodes decays with ti...

AI Technical Summary

Problems solved by technology

However, this solution also has two limitations: due to the lack of a centralized management model, the acquisition of node indirect trust needs to rely on a large amount of data sending and collection work, which increases the burden on nodes and may also cause high delays

It is difficult to guarantee the confidentiality, integrity, and convenience of accessing data during data storage in remote nodes, which may directly affect the security of the system and the actual application performance

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