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Updated: Aug 22, 2025

Effective Analysis of Human Exposure Conditions with Body-worn Dosimeters in the 2.4 GHz Band

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Differentially Private Occupancy Monitoring from WiFi Access Points.

Abbas Zaidi¹, Ritesh Ahuja¹, Cyrus Shahabi¹

¹USC Information Laboratory, University of Southern California, Los Angeles, USA.

IEEE International Conference on Mobile Data Management : MDM : [Proceedings]. IEEE International Conference on Mobile Data Management

|November 8, 2022

Summary

This summary is machine-generated.

This study introduces Differential Privacy to protect individual location privacy while monitoring building occupancy using WiFi data. The system accurately counts people in campus areas, minimizing privacy risks for enhanced public health surveillance.

Keywords:

WiFi access points differential privacy

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Last Updated: Aug 22, 2025

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Area of Science:

Computer Science
Public Health
Cybersecurity

Background:

Accurate building occupancy monitoring is crucial for limiting COVID-19 transmission.
Low adoption of contact tracing apps necessitates alternative digital tracking methods.
WiFi access point systems offer passive digital tracking but raise privacy concerns.

Purpose of the Study:

To examine the application of Differential Privacy for location privacy in WiFi-based occupancy monitoring.
To assess the effectiveness of Differential Privacy for point and range count queries in the CrowdMap system.
To develop discretization schemes for modeling user positions based on WiFi connections.

Main Methods:

Utilized the CrowdMap system for collecting aggregate WiFi connection statistics.
Developed and applied discretization schemes to infer user positions from WiFi access point data.
Implemented Differential Privacy techniques to protect individual location data during statistical reporting.

Main Results:

Accurate counts of occupants in specific campus building areas (labs, hallways, halls) were achieved.
Differential Privacy successfully minimized the risk of violating individual users' location privacy.
The proposed discretization schemes effectively modeled user locations using WiFi connection data.

Conclusions:

Differential Privacy is a viable method for enhancing privacy in WiFi-based occupancy monitoring systems.
The CrowdMap system, enhanced with Differential Privacy, can provide valuable occupancy data for public health.
Balancing accurate occupancy tracking with robust individual privacy protection is achievable.