CRJun 1, 2021

Toward a Secure Crowdsourced Location Tracking System

arXiv:2106.00217v11 citations
Originality Incremental advance
AI Analysis

This addresses security and privacy risks for users of Bluetooth trackers, but it is incremental as it builds on existing crowdsourced models.

The paper tackled the security and privacy vulnerabilities in commercial crowdsourced Bluetooth tracking systems by proposing a new design called SECrow, which preliminary evaluation shows to be practical, secure, and effective.

Low-energy Bluetooth devices have become ubiquitous and widely used for different applications. Among these, Bluetooth trackers are becoming popular as they allow users to track the location of their physical objects. To do so, Bluetooth trackers are often built-in within other commercial products connected to a larger crowdsourced tracking system. Such a system, however, can pose a threat to the security and privacy of the users, for instance, by revealing the location of a user's valuable object. In this paper, we introduce a set of security properties and investigate the state of commercial crowdsourced tracking systems, which present common design flaws that make them insecure. Leveraging the results of our investigation, we propose a new design for a secure crowdsourced tracking system (SECrow), which allows devices to leverage the benefits of the crowdsourced model without sacrificing security and privacy. Our preliminary evaluation shows that SECrow is a practical, secure, and effective crowdsourced tracking solution

Code Implementations1 repo
Foundations

The foundational work for this paper's niche, ranked by how specifically the neighbourhood builds on it — not by global fame.

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