Representation Learning for Sensor-based Device Pairing
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A4 Artikkeli konferenssijulkaisussa
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Date
2018-10-02
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en
Pages
4
508-511
508-511
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2018 IEEE International Conference on Pervasive Computing and Communications Workshops, PerCom Workshops 2018
Abstract
The emergence of on-body gadgets has introduced a novel research direction: unobtrusive and continuous device pairing. Existing approaches leveraged contextual information collected by sensors to generate secure communication keys. The secret information is represented throught hand-engineered features. In this paper, we propose a learning method based on Siamese neural networks to extract features that signify on-body context while separating off-body devices.Description
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Nguyen, N, Jähne-Raden, N, Kulau, U & Sigg, S 2018, Representation Learning for Sensor-based Device Pairing . in 2018 IEEE International Conference on Pervasive Computing and Communications Workshops, PerCom Workshops 2018 ., 8480412, IEEE, pp. 508-511, IEEE International Conference on Pervasive Computing and Communications Workshops, Athens, Greece, 19/03/2018 . https://doi.org/10.1109/PERCOMW.2018.8480412