Decentralized privacy preserving reputation evaluation method for crowd sensing

Abstract

The invention relates to a crowd sensing-oriented decentration privacy preservation reputation evaluation method, and belongs to the technical field of network data processing. According to the method, a reputation evaluation mechanism which can keep anonymity and can prevent a person from randomly modifying a reputation value is constructed by utilizing blind signature and ring signature technologies based on a crowd sensing scene of a block chain. Wherein the real identity of the user participating in the crowd sensing task is hidden by means of the anonymity of the block chain account, and the data demander issuing the sensing task scores the user according to the quality of the data provided by the user and issues the score on the block chain in a transaction form. A user who participates in a sensing task for multiple times allows to create a plurality of accounts, and secret transfer of a reputation value among different accounts is realized by using technologies such as ring signature and the like, so that inference attacks from a data demander are resisted. According to the identity authentication method and device, the relevance between the user account and the real identity of the user can be hidden, and the identity authentication of the user white washing attack can be resisted.

Description

technical field [0001] The invention relates to a reputation evaluation method for privacy preservation, in particular to a decentralized privacy preservation reputation evaluation method oriented to group intelligence, and belongs to the technical field of network data processing. Background technique [0002] In many data sharing scenarios, data demanders only need to obtain the data of the data owner, and do not need to know the real identity of the data owner. If data demanders need to use data from multiple data owners to complete specific analysis and computing tasks, they can usually use crowd sensing to collect data. [0003] In the application of crowd sensing, the data owners who participate in the sensing task usually share the real data directly with the data demanders, otherwise, the data demanders will not be able to obtain correct analysis results. At the same time, considering that data demanders do not need to know the real identity of the data owner, the d...

AI Technical Summary

Problems solved by technology

However, it does not consider how to allow data demanders to accurately assess the user's reputation without undermining privacy protection requirements

At the same time, the existing reputation mechanism that can protect user privacy is usually set up in a trusted third party, which manages the user's pseudonym and reputation value, but this condition is difficult to hold in reality

In addition, the existing reputation mechanism cannot effectively resist whitewashing attacks from users while ensuring privacy. Users may use anonymity to modify the reputation value at will

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