Time-bound Contextual Bio-ID Generation for Minimalist Wearables
Not on the map. Why?
Abstract (arXiv)
As wearable devices become increasingly miniaturized and powerful, a new opportunity arises for instant and dynamic device-to-device collaboration and human-to-device interaction. However, this progress presents a unique challenge: these minimalist wearables lack inherent mechanisms for real-time authentication, posing significant risks to data privacy and overall security. To address this, we introduce Proteus that realizes an innovative concept of time-bound contextual bio-IDs, which are generated from on-device sensor data and embedded into a common latent space. These bio-IDs act as a time-bound unique user identifier that can be used to identify the wearer in a certain context. Proteus enables dynamic and contextual device collaboration as well as robust human-to-device interaction. Our evaluations demonstrate the effectiveness of our method, particularly in the context of minimalist wearables.
Key facts. No citing papers in the map yet (data through 7 Oct 2026). Builds on 8 of its 26 references that are in the map. First posted on arXiv 1 Mar 2024.
Builds on
8 of 26 references.
References · 8
- 2020A Simple Framework for Contrastive Learning of Visual Representationscited by 11,979
- 2018Representation Learning with Contrastive Predictive Codingcited by 7,662
- 2019Momentum Contrast for Unsupervised Visual Representation Learningcited by 7,482
- 2020Exploring Simple Siamese Representation Learningcited by 2,853
- 2019An Introduction to Variational Autoencoderscited by 997
- 2015Adversarial Autoencoderscited by 359
- 2020Exploring Contrastive Learning in Human Activity Recognition for Healthcarecited by 73
- 2021EarGate: Gait-based User Identification with In-ear Microphonescited by 4
Built on by
Not cited yet.