Availability computing method of data published based on differential privacy

Abstract

The invention discloses an availability computing method of data published based on differential privacy and aims at collection data and relational data to respectively provide a DiffPart-based data availability computing method capable of protecting privacy and a DiffGen-based data availability computing method capable of protecting privacy, availability is defined, availability functions for measuring information losses of two methods are respectively given, some encrypted auxiliary data sets are published through a publisher, the auxiliary data sets are encrypted by a password system constructed on Z*n, the auxiliary data sets are verified in sequence to check whether data of the publisher are included in the auxiliary data sets correctly, and availability of the finally published data set is figured up by utilizing the auxiliary data sets. An experiment shows that the scheme has higher efficiency, and is mainly influenced by the number of data providers and the data scale.

Description

technical field [0001] The invention relates to a method for calculating the availability of data published based on differential privacy, and belongs to the technical field of information security. Background technique [0002] Service providers are usually able to collect a large amount of user data, and sometimes multiple providers of the same service may combine their accumulated data to support some special data mining tasks. For example, large hospitals across the country submit their data to a research group that will mine the data to model the spread of influenza. [0003] In the above process, how to protect the privacy of users is very important, which is the so-called joint data publishing problem for privacy protection. Many models have been proposed for this problem, such as K-anonymity and differential privacy. K-anonymity and its variants (l-diversity, t-closeness) generalize all records into several groups of records, making each record in each group indist...

AI Technical Summary

Problems solved by technology

Note that although the publisher obtains data from the provider, under a strong security model, the publisher cannot disclose the collected raw data to any data provider

Therefore, it is difficult for data providers or consumers to calculate availability

Although they can ask the publisher to calculate data availability (this is simple because the publisher owns both the original data and the published data) and inform them, the publisher is not necessarily trustworthy, and he can provide a fake higher availability.

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