Privacy-aware trajectory data publishing: an optimal efficient generalisation algorithm Online publication date: Tue, 05-Dec-2023
by Nattapon Harnsamut; Juggapong Natwichai
International Journal of Grid and Utility Computing (IJGUC), Vol. 14, No. 6, 2023
Abstract: With the increasing location-aware technologies that provide positioning services, it is easy to collect users' trajectory data. Such data could often contain sensitive information, i.e., private locations, private trajectory or path, and other sensitive attributes. In this paper, we propose a privacy preservation algorithm based on LKC-privacy model to protect the privacy attacks of trajectory data publishing. Not only can the data utility be maintained effectively by the data generalisation approach, but this algorithm can also reduce the computing time of the look-up table creation which is one of the highest computational processes. Our proposed algorithm is evaluated with extensive experiments. From the experiments, the enhanced-LT algorithm performance in terms of the execution time outperforms the baseline LT algorithm by 48.5% on average. The results show that our proposed algorithm returns not only the optimal solution but also highly efficient computation times.
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