4 papers
What is the Cost of Differential Privacy for Deep Learning-Based Trajectory Generation?
Erik Buchholz, Natasha Fernandes, David D. Nguyen +3
While location trajectories offer valuable insights, they also reveal sensitive personal information. Differential Privacy (DP) offers formal protection, but achieving a favourable…
Demystifying Trajectory Recovery From Ash: An Open-Source Evaluation and Enhancement
Nicholas D'Silva, Toran Shahi, Ãyvind Timian Dokk Husveg +3
Once analysed, location trajectories can provide valuable insights beneficial to various applications. However, such data is also highly sensitive, rendering them susceptible to pr…
Synthetic Trajectory Generation Through Convolutional Neural Networks
Jesse Merhi, Erik Buchholz, Salil S. Kanhere
Location trajectories provide valuable insights for applications from urban planning to pandemic control. However, mobility data can also reveal sensitive information about individ…
SoK: Can Trajectory Generation Combine Privacy and Utility?
Erik Buchholz, Alsharif Abuadbba, Shuo Wang +2
While location trajectories represent a valuable data source for analyses and location-based services, they can reveal sensitive information, such as political and religious prefer…