http://g7ee5otfyict57k24vjujuqzi6pd7iwvnsry2mt3svsgwzn6o6iynsad.onion/popets/2023/popets-2023-0118.php
The motivation of this work is to report our experience of addressing the practical problem of secure training and inference of models for urban sensing problems, e.g., traffic congestion estimation, or air pollution monitoring in large cities, where data can be contributed by rival fleet companies while balancing the privacy-accuracy trade-offs using MPC-based techniques.Our first contribution is to design a custom ML model for this task that can be efficiently trained...