Paper accepted at IEEE Transactions on Vehicular Technology, 2020

Dinusha Vatsalan had a paper accepted at IEEE Transactions on Vehicular Technology, 2020. Publishing or collecting individuals’ mobility data poses serious privacy concerns. Instead of perturbing data by adding noise to the raw location data to preserve privacy of individuals, we propose an approach that achieves privacy-preservation at the statistics level of aggregating mobility datasets with the probabilistic data structure Count-Min Sketch(CMS), which has been widely used to provide efficient statistic functions with a tunable error bound.

• Qing Yang, Yiran Shen, Dinusha Vatsalan, Jianpei Zhang, Dali Kaafar, and Wen Hu, “P4Mobi: A Probabilistic Privacy-PreservingFramework for Publishing Mobility Datasets“, IEEE Transactions on Vehicular Technology, 2020