The Method of Location Privacy Protection Based on Grid Identifier Matching

ZHANG Shaobo; LIU Qin; WANG Guojun

doi:10.11999/JEIT160350

Volume 38 Issue 9

Sep. 2016

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Article Navigation > Journal of Electronics & Information Technology > 2016 > 38(9): 2173-2179

ZHANG Shaobo, LIU Qin, WANG Guojun. The Method of Location Privacy Protection Based on Grid Identifier Matching[J]. Journal of Electronics & Information Technology, 2016, 38(9): 2173-2179. doi: 10.11999/JEIT160350

Citation:

ZHANG Shaobo, LIU Qin, WANG Guojun. The Method of Location Privacy Protection Based on Grid Identifier Matching[J]. Journal of Electronics & Information Technology, 2016, 38(9): 2173-2179. doi: 10.11999/JEIT160350

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The Method of Location Privacy Protection Based on Grid Identifier Matching

doi: 10.11999/JEIT160350 cstr: 32379.14.JEIT160350

Funds:

The National Natural Science Foundation of China (61472451, 61272151, 61402161), The Fundamental Research Funds for the Central Universities of Central South University (2016zzts058)

Received Date: 2016-04-12
Rev Recd Date: 2016-07-18
Publish Date: 2016-09-19

Abstract

Abstract

The model based on fully-trusted third party is a major model for location privacy protection in location-based services, but the model has some risk of exposing privacy. In this paper, a location privacy protection method based on Grid Identifier Matching (GIM) is proposed. In this method the user first divides the query area into grid and combines the order-preserving symmetric encryption and K-anonymity mechanism. Then, the K-anonymity paradigm is formed in anonymizer. Finally, the query results are returned to users by utilizing GIM. In the query process, the anonymizer dose not have any knowlegdge about a users real location, which can enhance the users location privacy. Meanwhile, the anonymizer only does simple comparison and matching operations, which relieves effectively is performance bottleneck of the anonymizer. Security analysis shows that the proposed approach can effectively protect the users location privacy. Experimental evaluations show that the proposed approach can decrease processing time overhead of the anonymizer.
- Location privacy,
- Grid Identifier Matching (GIM),
- Order-preserving symmetric encryption,
- K- anonymity

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References(21)

References

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