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Wearable Ubiquitous Technol."],"published-print":{"date-parts":[[2023,9,27]]},"abstract":"<jats:p>Technical advances in the smart device market have fixated smartphones at the heart of our lives, warranting an ever more secure means of authentication. Although most smartphones have adopted biometrics-based authentication, after a couple of failed attempts, most users are given the option to quickly bypass the system with passcodes. To add a layer of security, two-factor authentication (2FA) has been implemented but has proven to be vulnerable to various attacks. In this paper, we introduce VibPath, a simultaneous 2FA scheme that can understand the user's hand neuromuscular system through touch behavior. VibPath captures the individual's vibration path responses between the hand and the wrist with the attention-based encoder-decoder network, authenticating the genuine users from the imposters unobtrusively. In a user study with 30 participants, VibPath achieved an average performance of 0.98 accuracy, 0.99 precision, 0.98 recall, 0.98 f1-score for user verification, and 94.3% accuracy for user identification across five passcodes. Furthermore, we also conducted several extensive studies, including in-the-wile, permanence, vulnerability, usability, and system overhead studies, to assess the practicability and viability of the VibPath from multiple aspects.<\/jats:p>","DOI":"10.1145\/3610894","type":"journal-article","created":{"date-parts":[[2023,9,27]],"date-time":"2023-09-27T15:45:03Z","timestamp":1695829503000},"page":"1-26","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":9,"title":["VibPath"],"prefix":"10.1145","volume":"7","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-4284-6728","authenticated-orcid":false,"given":"Seokmin","family":"Choi","sequence":"first","affiliation":[{"name":"University at Buffalo, Department of Computer Science and Engineering, Buffalo, NY, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7172-9788","authenticated-orcid":false,"given":"Junghwan","family":"Yim","sequence":"additional","affiliation":[{"name":"University at Buffalo, Department of Computer Science and Engineering, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6809-1143","authenticated-orcid":false,"given":"Se Jun","family":"Kim","sequence":"additional","affiliation":[{"name":"University at Buffalo, Department of Computer Science and Engineering, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1812-4234","authenticated-orcid":false,"given":"Yincheng","family":"Jin","sequence":"additional","affiliation":[{"name":"University at Buffalo, Department of Computer Science and Engineering, Buffalo, NY, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8697-1817","authenticated-orcid":false,"given":"Di","family":"Wu","sequence":"additional","affiliation":[{"name":"Hunan University, School of Design, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3020-3736","authenticated-orcid":false,"given":"Zhanpeng","family":"Jin","sequence":"additional","affiliation":[{"name":"South China University of Technology, School of Future Technology, China and University at Buffalo, Department of Computer Science and Engineering, USA"}]}],"member":"320","published-online":{"date-parts":[[2023,9,27]]},"reference":[{"key":"e_1_2_1_1_1","unstructured":"2022. 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