Perturbed-Location Mechanism for Increased User-Location Privacy in Proximity Detection and Digital Contact-Tracing...

Area of Science:

• Computer Science
• Ubiquitous Computing
• Information Security

Background:

• Future social networks increasingly depend on sensing data from mobile and wearable devices.
• Location data is crucial for enabling location-based and proximity-detection services, such as digital contact tracing and social networking.
• Protecting user location privacy is a significant challenge in proximity-detection architectures.

Purpose of the Study:

• To propose a location-perturbation mechanism for multi-floor buildings.
• To enhance user location privacy while maintaining effective proximity-detection capabilities.
• To investigate the trade-off between privacy and utility in location-based services.

Main Methods:

• Developed a location-perturbation mechanism for multi-floor environments.
• Assumed users have control over their location data and access to floor-map information.
• Devices can adjust location disclosure accuracy.
• Conducted simulation-based evaluations in multi-floor building scenarios with hotspot regions.

Main Results:

• The proposed mechanism significantly protects user location privacy.
• The system maintains very good proximity-detection capabilities.
• Detailed simulations demonstrate the effectiveness in complex building environments.
• The trade-off between privacy and utility was thoroughly investigated.

Conclusions:

• The developed location-perturbation mechanism offers a viable solution for privacy-preserving proximity-detection services in multi-floor buildings.
• User control over location data and adjustable accuracy are key components.
• The research provides valuable insights into balancing privacy and utility in location-aware systems.