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The development of location-based services and mobile devices has lead to an increase in the location data. Through the data mining process, some valuable information can be discovered from location data. In the other words, an attacker may also extract some private (sensitive) information of the user and this may make threats against the user privacy. Therefore, location privacy protection becomes an important requirement to the success in the development of location-based services. In this paper, we propose a grid-based approach as well as an algorithm to guarantee k-anonymity, a well-known privacy protection approach, in a location database. The proposed approach considers only the information that has significance for the data mining process while ignoring the un-related information. The experiment results show the effectiveness of the proposed approach in comparison with the literature ones.

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Article Details

Issue: Vol 3 No SI1 (2020): Special Issue: Computer Science and Engineering
Page No.: SI82-SI94
Published: Dec 4, 2020
Section: Research article

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Creative Commons License

Copyright: The Authors. This is an open access article distributed under the terms of the Creative Commons Attribution License CC-BY 4.0., which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

 How to Cite
Truong, A. (2020). Privacy Preserving Spatio-Temporal Databases Based on k-Anonymity. Science & Technology Development Journal - Engineering and Technology, 3(SI1), SI82-SI94.

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