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DeepAuth : in-situ authentication for smartwatches via deeply learned behavioural biometrics
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Xiaoxuan Lu , Chris, Du, Bowen, Zhao, Peijun, Wen, Hongkai, Shen, Yiran, Markham, Andrew and Trigoni, Niki (2018) DeepAuth : in-situ authentication for smartwatches via deeply learned behavioural biometrics. In: ISWC '18 : International Symposium on Wearable Computers, Singapore, 8–12 Oct 2018. Published in: ISWC '18: Proceedings of the 2018 ACM International Symposium on Wearable Computers pp. 204-207. ISBN 9781450359672. doi:10.1145/3267242.3267252
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WRAP-DeepAuth-in-situ-authentication-smartwatches-Wen-2018.pdf - Accepted Version - Requires a PDF viewer. Download (778Kb) | Preview |
Official URL: https://doi.org/10.1145/3267242.3267252
Abstract
This paper proposes DeepAuth, an in-situ authentication framework that leverages the unique motion patterns when users entering passwords as behavioural biometrics. It uses a deep recurrent neural network to capture the subtle motion signatures during password input, and employs a novel loss function to learn deep feature representations that are robust to noise, unseen passwords, and malicious imposters even with limited training data. DeepAuth is by design optimised for resource constrained platforms, and uses a novel sub-RNNs architecture to slim inference down to run in real-time on off-the-shelf smartwatches. Extensive experiments with real-world data show that DeepAuth outperforms the state-of-the-art significantly in both authentication performance and cost, offering real-time authentication on a variety of smartwatches.
| Item Type: | Conference Item (Paper) | ||||||
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| Subjects: | Q Science > QA Mathematics > QA76 Electronic computers. Computer science. Computer software T Technology > TK Electrical engineering. Electronics Nuclear engineering |
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| Divisions: | Faculty of Science, Engineering and Medicine > Science > Computer Science | ||||||
| Library of Congress Subject Headings (LCSH): | Smartwatches, Computers -- Access control -- Passwords, Biometry -- Computer programs | ||||||
| Journal or Publication Title: | ISWC '18: Proceedings of the 2018 ACM International Symposium on Wearable Computers | ||||||
| Publisher: | ACM | ||||||
| ISBN: | 9781450359672 | ||||||
| Official Date: | October 2018 | ||||||
| Dates: |
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| Page Range: | pp. 204-207 | ||||||
| DOI: | 10.1145/3267242.3267252 | ||||||
| Status: | Peer Reviewed | ||||||
| Publication Status: | Published | ||||||
| Reuse Statement (publisher, data, author rights): | © Copyright held by the owner/author(s). Publication rights licensed to ACM. This is the author's version of the work. It is posted here for your personal use. Not for redistribution. The definitive Version of Record was published in SWC’18, October 08–12, 2018, Singapore | ||||||
| Access rights to Published version: | Restricted or Subscription Access | ||||||
| Date of first compliant deposit: | 7 August 2018 | ||||||
| Date of first compliant Open Access: | 7 August 2018 | ||||||
| Conference Paper Type: | Paper | ||||||
| Title of Event: | ISWC '18 : International Symposium on Wearable Computers | ||||||
| Type of Event: | Other | ||||||
| Location of Event: | Singapore | ||||||
| Date(s) of Event: | 8–12 Oct 2018 | ||||||
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