Balancing Functionality and GDPR-Driven Privacy in ISAC Trajectory Sharing
2026-04-09 • Networking and Internet Architecture
Networking and Internet Architecture
AI summaryⓘ
The authors address privacy concerns in systems that share movement paths (trajectories) to improve communication and sensing. They propose a new method that limits how precisely others can figure out these paths, ensuring a guaranteed minimum uncertainty in the data shared. Their approach adapts to different conditions and prevents reconstructing any part of the path too accurately, while still allowing useful data for tasks like predicting movement. Tests on real data showed this method keeps privacy leakage low and works well with regulations like GDPR.
Integrated Sensing and Communications (ISAC)trajectory sharingprivacyGDPRdata minimisationFisher Information Density (FID)Privacy Leak Ratio (PLR)beamformingresource allocationmovement prediction
Authors
Zexin Fang, Bin Han, Zhuojun Tian, Hans D. Schotten
Abstract
Integrated Sensing and Communications (ISAC) enables trajectory sharing that enhances beamforming, resource allocation, and cooperative perception, yet raises fundamental privacy concerns under the General Data Protection Regulation (GDPR) data minimisation principle. This paper proposes a Fisher Information Density (FID)-constrained trajectory sharing framework that enforces a local lower bound on estimation uncertainty, providing hard, quantifiable privacy guarantees by construction. Unlike fixed-noise approaches, the proposed method bounds the Privacy Leak Ratio (PLR) regardless of sensing power or adversarial post-processing, ensuring that no trajectory segment can be reconstructed beyond a prescribed accuracy threshold. Simulations on the OpenTraj dataset demonstrate that the framework keeps the average PLR below 20-25% and the maximum leakage segment duration under 2-2.5 s, while preserving data utility for downstream tasks such as movement prediction. The resulting criterion is interpretable, model-agnostic, and compatible with GDPR-compliant ISAC system design.