TY - GEN
T1 - Usable User Authentication on a Smartwatch using Vibration
AU - Lee, Sunwoo
AU - Choi, Wonsuk
AU - Lee, Dong Hoon
N1 - Funding Information:
This work was supported by the National Research Foundation of Korea (NRF) Grant funded by the Korean Government Ministry of Science and ICT (MSIT) under Grant NRF-2021R1A2C2014428.
Publisher Copyright:
© 2021 ACM.
PY - 2021/11/12
Y1 - 2021/11/12
N2 - Smartwatches have come into wide use in recent years, and a number of smartwatch applications that improve convenience and user health are being developed and introduced constantly. Moreover, the latest smartwatches are now designed to operate without their paired smartphones, and as such, it is necessary for smartwatches to independently authenticate users. In these current devices, personal identification numbers (PIN) or patterns are entered to authenticate users, but these methods require inconvenient interaction for the user and are not highly secure. Particularly relevant to smartwatch technology, even user authentication based on biometric information needs either special sensors capable of measuring biometric information or user interaction. In this paper, we propose a usable method for user authentication on smartwatches without additional devices. Based on the fact that vibration is absorbed, reflected, and propagated differently according to the physical structure of each human body, our method is designed as a challenge-response scheme, in which the challenge is a random sequence of multiple vibration types that are already built into current smartwatches. The responses to vibrations are measured by the default gyroscope and accelerometer sensors in smartwatches. Moreover, our method is the first working model for commercial smartwatch models with low specifications when vibrating and measuring responses. We evaluated our method using a commercial smartwatch, and the results show that our method is able to authenticate a user with an equal error rate (EER) of 1.37%.
AB - Smartwatches have come into wide use in recent years, and a number of smartwatch applications that improve convenience and user health are being developed and introduced constantly. Moreover, the latest smartwatches are now designed to operate without their paired smartphones, and as such, it is necessary for smartwatches to independently authenticate users. In these current devices, personal identification numbers (PIN) or patterns are entered to authenticate users, but these methods require inconvenient interaction for the user and are not highly secure. Particularly relevant to smartwatch technology, even user authentication based on biometric information needs either special sensors capable of measuring biometric information or user interaction. In this paper, we propose a usable method for user authentication on smartwatches without additional devices. Based on the fact that vibration is absorbed, reflected, and propagated differently according to the physical structure of each human body, our method is designed as a challenge-response scheme, in which the challenge is a random sequence of multiple vibration types that are already built into current smartwatches. The responses to vibrations are measured by the default gyroscope and accelerometer sensors in smartwatches. Moreover, our method is the first working model for commercial smartwatch models with low specifications when vibrating and measuring responses. We evaluated our method using a commercial smartwatch, and the results show that our method is able to authenticate a user with an equal error rate (EER) of 1.37%.
KW - authentication
KW - biometrics
KW - signal processing
KW - smartwatches
UR - http://www.scopus.com/inward/record.url?scp=85119331257&partnerID=8YFLogxK
U2 - 10.1145/3460120.3484553
DO - 10.1145/3460120.3484553
M3 - Conference contribution
AN - SCOPUS:85119331257
T3 - Proceedings of the ACM Conference on Computer and Communications Security
SP - 304
EP - 319
BT - CCS 2021 - Proceedings of the 2021 ACM SIGSAC Conference on Computer and Communications Security
PB - Association for Computing Machinery
T2 - 27th ACM Annual Conference on Computer and Communication Security, CCS 2021
Y2 - 15 November 2021 through 19 November 2021
ER -