Moving trajectory data privacy protection matching method based on multi-iteration filtering

Abstract

The invention provides a moving trajectory data privacy protection matching method based on multi-iteration filtering. The method comprises the following steps: mapping moving track data to a Bloom filter by two parties owned by the data, roughly matching and calculating based on the maximum distance of 1-value bits of the Bloom filter, and accurately matching and calculating based on the minimumvalue of a common bit with the bit value of 1 in exchange bits of the Bloom filter. Third-party participation is not needed, and a matching result can be obtained only by agreeing specific implementation parameters and processing the exchange data and the existing data by the two parties; a matching process based on similarity calculation is realized on a Bloom filter with irreversibility, so thatthe confidentiality of original data can be ensured. And the confidentiality of the original data is further improved. Quick elimination of unmatched data is realized, and the data calculation amountand exchange amount are greatly reduced, so that the matching operation efficiency is improved.

Description

technical field [0001] The invention relates to the research field of spatial data privacy protection technology, in particular to a mobile trajectory data privacy protection matching method based on multiple iterative filtering. Background technique [0002] With the rapid development of mobile communication technology, smart phones that provide positioning services have been widely popularized, and a large amount of mobile trajectory data with spatiotemporal characteristics has been generated. Analyzing the movement trajectory data to discover potential and valuable mobility rules has important reference value for applications such as analysis and prediction of human or animal related behavior habits, and disease transmission control. At present, there is a very serious common problem in many mobile trajectory data analysis applications: data bias. That is, analysis applications usually use a single source of movement trajectory data, and it is difficult to achieve a comp...

AI Technical Summary

Problems solved by technology

[0004] The purpose of the present invention is to provide a mobile trajectory data privacy protection matching method based on multiple iterative filtering, which uses multiple iterative filtering without third-party participation, and only requires both data owners to directly perform multiple iterative filtering for mobile trajectory data privacy Protected matching, which solves the problem of poor user location privacy and security

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