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ACM Interact. Mob. Wearable Ubiquitous Technol."],"published-print":{"date-parts":[[2018,9,18]]},"abstract":"<jats:p>User authentication on smart devices is indispensable to keep data privacy and security. It is especially significant for emerging wearable devices such as smartwatches considering data sensitivity in them. However, conventional authentication methods are not applicable for wearables due to constraints of size and hardware, which makes present wearable devices lack convenient, secure and low-cost authentication schemes. To tackle this problem, we reveal a novel biometric authentication mechanism which makes use of sounds of human dental occlusion (i.e., tooth click). We demonstrate its feasibility by comprehensive measurement study, and design a prototype-BiLock with two Android platforms. Extensive real-world experiments have been conducted to evaluate the accuracy, robustness and security of BiLock in different environments. The results show that BiLock can achieve less than 5% average false reject rate and 0.95% average false accept rate even in a noisy environment. Comparative experiments also demonstrate that BiLock possesses advantages in robustness to noise and security against replay and observation attacks over existing voiceprinting schemes.<\/jats:p>","DOI":"10.1145\/3264962","type":"journal-article","created":{"date-parts":[[2018,9,19]],"date-time":"2018-09-19T11:58:41Z","timestamp":1537358321000},"page":"1-20","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":38,"title":["BiLock"],"prefix":"10.1145","volume":"2","author":[{"given":"Yongpan","family":"Zou","sequence":"first","affiliation":[{"name":"College of Computer Science and Software Engineering, Shenzhen University"}]},{"given":"Meng","family":"Zhao","sequence":"additional","affiliation":[{"name":"College of Computer Science and Software Engineering, Shenzhen University"}]},{"given":"Zimu","family":"Zhou","sequence":"additional","affiliation":[{"name":"Computer Engineering and Networks Laboratory, ETH Zurich"}]},{"given":"Jiawei","family":"Lin","sequence":"additional","affiliation":[{"name":"College of Computer Science and Software Engineering, Shenzhen University"}]},{"given":"Mo","family":"Li","sequence":"additional","affiliation":[{"name":"School of Computer Science and Engineering, Nanyang Technological University"}]},{"given":"Kaishun","family":"Wu","sequence":"additional","affiliation":[{"name":"College of Computer Science and Software Engineering, Shenzhen University"}]}],"member":"320","published-online":{"date-parts":[[2018,9,18]]},"reference":[{"key":"e_1_2_2_1_1","doi-asserted-by":"publisher","DOI":"10.1007\/s00034-017-0524-7"},{"key":"e_1_2_2_2_1","unstructured":"Apple Inc. 2017. iPhone X. https:\/\/www.apple.com\/iphone-x\/. 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