A Survey of Wearable Devices Pairing Based on Biometric Signals
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Abstract (arXiv)
With the growth of wearable devices, which are usually constrained in computational power and user interface, this pairing has to be autonomous. Considering devices that do not have prior information about each other, a secure communication should be established by generating a shared secret key derived from a common context between the devices. Context-based pairing solutions increase the usability of wearable device pairing by eliminating any human involvement in the pairing process. This is possible by utilizing onboard sensors (with the same sensing modalities) to capture a common physical context (e.g., body motion, gait, heartbeat, respiration, and EMG signal). A wide range of approaches has been proposed to address autonomous pairing in wearable devices. This paper surveys context-based pairing in wearable devices by focusing on the signals and sensors exploited. We review the steps needed for generating a common key and provide a survey of existing techniques utilized in each step.
Key facts. Cited by 3 papers in the map (data through 14 Oct 2026). First posted on arXiv 24 Jul 2021.
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Citing papers per year: 2024: 1; 2025: 1; 2026: 1.
3 papers.
- 2024Differentially Private Integrated Decision Gradients (IDG-DP) for Radar-based Human Activity Recognitioncited by 2
- 2025UL-DD: A Multimodal Drowsiness Dataset Using Video, Biometric Signals, and Behavioral Datacited by 1
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- 2026Sign in the Air to Unlock: An Interface for authentication in Virtual and Augmented Reality Powered by Point-Voxel Cross-Attention Network1 Jul 2026
- 2025UL-DD: A Multimodal Drowsiness Dataset Using Video, Biometric Signals, and Behavioral Data16 Jul 2025
- 2024Differentially Private Integrated Decision Gradients (IDG-DP) for Radar-based Human Activity Recognition4 Nov 2024