TL;DR
Next2You introduces a Wi-Fi channel state information-based copresence detection method that overcomes previous limitations, providing accurate, real-time, and attack-resistant proximity verification on standard smartphones.
Contribution
The paper presents Next2You, a novel CSI-based copresence detection scheme that works reliably in low-entropy and challenging environments without requiring special sensors.
Findings
Error rates below 4% in various scenarios
Effective in low-entropy and adjacent environments
Operates reliably in real-time on smartphones
Abstract
Context-based copresence detection schemes are a necessary prerequisite to building secure and usable authentication systems in the Internet of Things (IoT). Such schemes allow one device to verify proximity of another device without user assistance utilizing their physical context (e.g., audio). The state-of-the-art copresence detection schemes suffer from two major limitations: (1) they cannot accurately detect copresence in low-entropy context (e.g., empty room with few events occurring) and insufficiently separated environments (e.g., adjacent rooms), (2) they require devices to have common sensors (e.g., microphones) to capture context, making them impractical on devices with heterogeneous sensors. We address these limitations, proposing Next2You, a novel copresence detection scheme utilizing channel state information (CSI). In particular, we leverage magnitude and phase values…
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