Research article Open Access Logo

Privacy Preserving Spatio-Temporal Databases Based on k-Anonymity

Anh Tuan Truong 1, *
  1. HoChiMinh City University of Technology
Correspondence to: Anh Tuan Truong, HoChiMinh City University of Technology. Email: [email protected].
Published: 2020-12-04

Online metrics


Statistics from the website

  • Abstract Views: 0
  • Galley Views: 0

Statistics from Dimensions

This article is published with open access by Viet Nam National University, Ho Chi Minh City, Viet Nam. This article is distributed under the terms of the Creative Commons Attribution License (CC-BY 4.0) which permits any use, distribution, and reproduction in any medium, provided the original author(s) and the source are credited. 

Abstract

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.

Comments