ArticleSensors (Basel, Switzerland)2022
Perturbed-Location Mechanism for Increased User-Location Privacy in Proximity Detection and Digital Contact-Tracing Applications.
Article in Sensors (Basel, Switzerland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed.
- HydraGAN: A Cooperative Agent Model for Multi-Objective Data Generation.ACM transactions on intelligent systems and technology · 2024Article
- Privacy by Projection: Federated Population Density Estimation by Projecting on Random Features.Proceedings on Privacy Enhancing Technologies. Privacy Enhancing Technologies Symposium · 2023Article
- Q-Learning-Based Pending Zone Adjustment for Proximity Classification.Sensors (Basel, Switzerland) · 2023Article
- Sensor Networks: Physical and Social Sensing in the IoT.Sensors (Basel, Switzerland) · 2023Article
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Authors and funding
3 authors.
Funding
Abstract
Future social networks will rely heavily on sensing data collected from users' mobile and wearable devices. A crucial component of such sensing will be the full or partial access to user's location data, in order to enable various location-based and proximity-detection-based services. A timely example of such applications is the digital contact tracing in the context of infectious-disease control and management. Other proximity-detection-based applications include social networking, finding nearby friends, optimized shopping, or finding fast a point-of-interest in a commuting hall. Location information can enable a myriad of new services, among which we have proximity-detection services. Addressing efficiently the location privacy threats remains a major challenge in proximity-detection architectures. In this paper, we propose a location-perturbation mechanism in multi-floor buildings which highly protects the user location, while preserving very good proximity-detection capabilities. The proposed mechanism relies on the assumption that the users have full control of their location information and are able to get some floor-map information when entering a building of interest from a remote service provider. In addition, we assume that the devices own the functionality to adjust to the desired level of accuracy at which the users disclose their location to the service provider. Detailed simulation-based results are provided, based on multi-floor building scenarios with hotspot regions, and the tradeoff between privacy and utility is thoroughly investigated.
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Registered trials
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