Location Anonymity in Horizontally Partitioned Spatio-Temporal Data
İnan, Ali and Saygın, Yücel (2006) Location Anonymity in Horizontally Partitioned Spatio-Temporal Data. (Submitted)
Wireless service providers can observe and store location information of their customers with high precision. Collected time-stamped location information is regarded as spatio-temporal data due to its time and space dimensions and, by its nature, is highly vulnerable to misuse. Privacy issues related to collection, use and distribution of individuals’ location information are the main obstacles hampering utilization of spatio-temporal data. Suppressing identifiers from the data does not suffice since movement trajectories can easily be linked to individuals using publicly available information such as home or work addresses. In this paper, we propose a method to achieve anonymity in horizontally partitioned spatio-temporal datasets distributed among two or more data holders. This method blocks certain attacks against previous work in the area. Our motivating example is a group of telecommunication companies who want to release location observations of their customers to government agencies for the purpose of traffic analysis. Experiments conducted to measure the information content of the anonymized datasets show that our distributed anonymization method yields %12 to %100 information gain compared to locally anonymized and then aggregated datasets depending on the anonymity requirements.
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