Securely and unobtrusively authenticating a user is an important problem given the pervasiveness of smartphones. Existing approaches, such as password, fingerprints, or facial recognition, are vulnerable to various attacks, and/or degrade usability. To overcome this problem, we propose Shakespeer, which differentiates users based on uniqueness in the propagation of haptic vibrations through hand, forearm muscles and bones. These vibrations are generated by the user's smartphone and sensed by their smartphone and smartwatch. The unobtrusive haptic vibrational response makes this biometric feature hard to be replicated. Meanwhile, it provides the co-presence detection function, which allows the devices to confirm the co-presence on the user's body. We implement Shakespeer using smartphones and smartwatches and tested it across 32 subjects under real-world settings. From our preliminary exploratory evaluation, Shakespeer achieves an equal error rate (EER) of 0.59 %, demonstrating its feasibility.
|Title of host publication||2022 26th International Conference on Pattern Recognition, ICPR 2022|
|Publisher||Institute of Electrical and Electronics Engineers Inc.|
|Number of pages||7|
|Publication status||Published - 2022|
|Event||26th International Conference on Pattern Recognition, ICPR 2022 - Montreal, Canada|
Duration: 2022 Aug 21 → 2022 Aug 25
|Name||Proceedings - International Conference on Pattern Recognition|
|Conference||26th International Conference on Pattern Recognition, ICPR 2022|
|Period||22/8/21 → 22/8/25|
Bibliographical notePublisher Copyright:
© 2022 IEEE.
All Science Journal Classification (ASJC) codes
- Computer Vision and Pattern Recognition