Jean-François Determe

CR
3papers
2citations
Novelty32%
AI Score33

3 Papers

0.4CRJun 4
Opportunities and Challenges in Securely Reusing and Repurposing Mobile Devices

Adelin Roty, Jan Tobias Mühlberg, Jean-François Determe

An estimated 5.3 billion mobile phones became electronic waste in 2022. Many of these devices can be repurposed and used in different contexts to extend their lifetime and to reduce ecological impacts. An often overlooked aspect of smartphone reuse is cybersecurity: these devices embed hardware-backed security mechanisms that rely on vendor-controlled provisioning and are designed for a fixed device lifecycle. In this paper, we investigate whether security mechanisms and guarantees remain effective when devices are repurposed outside their original ecosystem. We explore security features in a PinePhone, an open-hardware smartphone, and focus on three core security aspects: boot chain integrity, isolation provided by the Trusted Execution Environment, and the protection of hardware-bound secrets. Our experiments simulate realistic repurposing scenarios and highlight the complexity of reconstructing trust anchors. We generalize our observations to infer requirements for secure repurposing and illustrate how vendor locked mechanisms hinder the repurposing of a majority of discarded devices.

SYOct 20, 2020
Monitoring Large Crowds With WiFi: A Privacy-Preserving Approach

Jean-François Determe, Sophia Azzagnuni, Utkarsh Singh et al.

This paper presents a crowd monitoring system based on the passive detection of probe requests. The system meets strict privacy requirements and is suited to monitoring events or buildings with a least a few hundreds of attendees. We present our counting process and an associated mathematical model. From this model, we derive a concentration inequality that highlights the accuracy of our crowd count estimator. Then, we describe our system. We present and discuss our sensor hardware, our computing system architecture, and an efficient implementation of our counting algorithm -- as well as its space and time complexity. We also show how our system ensures the privacy of people in the monitored area. Finally, we validate our system using nine weeks of data from a public library endowed with a camera-based counting system, which generates counts against which we compare those of our counting system. This comparison empirically quantifies the accuracy of our counting system, thereby showing it to be suitable for monitoring public areas. Similarly, the concentration inequality provides a theoretical validation of the system.

CRSep 21, 2020
MAC Address Anonymization for Crowd Counting

Jean-François Determe, Sophia Azzagnuni, François Horlin et al.

Research has shown that counting WiFi packets called probe requests (PRs) implicitly provides a proxy for the number of people in an area. In this paper, we discuss a crowd counting system involving WiFi sensors detecting PRs over the air, then extracting and anonymizing their media access control (MAC) addresses using a hash-based approach. This paper discusses an anonymization procedure and shows time-synchronization inaccuracies among sensors and hashing collision rates to be low enough to prevent anonymization from interfering with counting algorithms. In particular, we derive an approximation of the collision rate of uniformly distributed identifiers, with analytical error bounds.