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Jordi Forné

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Open access 2026

On the Adaptation of Trajectory Generative Models to Enforce Differential Privacy Through Gradient Perturbation

This paper investigates whether state-of-the-art deep learning trajectory generators can be adapted to satisfy differential privacy (DP) while retaining usable utility, and introduces RouteMIA, the first closed-box membership inference attack tailored to synthetic trajectories.

Víctor Rubio-Jornet, Javier Parra-Arnau, Jordi Forné · 0 citations

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