User locus privacy protection method based on space sequence data analysis

A data analysis and user trajectory technology, applied in the field of information security, can solve the problem that it is difficult to ensure that the statistical characteristics and clustering characteristics of location and trajectory data in spatial big data remain unchanged.
CN105701418AActive Publication Date: 2016-06-22XI AN JIAOTONG UNIV
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
XI AN JIAOTONG UNIV
Publication Date
2016-06-22

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Abstract

The invention discloses a user locus privacy protection method based on space sequence data analysis; the method comprises the following steps: carrying out cluster analysis for space sequence data of each mobile user so as to obtain interested points and zones of each user; carrying out iteration for the interested points and zones of all users in an assignment area according to time line, thus obtaining user common interested areas in different time scopes; using a position random exchange method to realize dynamic protection of the user locus privacy in each common interested area. The novel method can analyze and process the locus data in time and space dimensions, thus protecting privacy while ensuring statistics characteristic and cluster characteristic to be unchanged, satisfying application demands in space big data issue and shearing time zone analysis (area comparison analysis, population density analysis, traffic status analysis), and balancing privacy protection and data availability contradiction.
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Description

technical field

[0001] The invention relates to the technical field of information security, in particular to a method for protecting user track privacy. Background technique

[0002] With the development of Location Based Service (LBS) and the popularity of smart devices, a large amount of spatial data is generated. Through real-time release or sharing of spatial data, it can not only provide convenience for personal life, but also provide services for government decision-making and enterprise production. However, when users use spatial data to obtain services, they will inevitably leave a large number of records on the data server, and the context information attached to these user records often contains the user's personal sensitive information. In the process of data publishing and sharing, in addition to how to analyze from the perspective of data, it is also necessary to consider the consequences of the analysis on its statistics and mining; the ideal privacy protecti...

Claims

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