Abstract
In the actual production environment, a large number of data sets to be protected are non-single type attribute data sets, that is, mixed data sets.In view of the above problems, this project proposes a fast clustering privacy protection research method based on blockchain mixed data. This method is mainly for complex data types, cloud environment for different data types with different measurement method, the difference of the hybrid data set by calculation of each sample point neighborhood density and relative distance, divided into k density and relative distance far sample points as the initial clustering center, clustering, complete and upload them to block chain. For the generated clustering results, the numerical clustering centers are calculated, and the set of attribute values of non-numerical data is generated, which ensures that each user can correctly obtain the iterative process and the final clustering centers, and reduces the error rate of data.
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