EmgAuth: Unlocking Smartphones with EMG Signals

TL;DR

EmgAuth is a novel EMG-based smartphone unlocking system using Siamese networks and data augmentation, achieving high accuracy and robustness without calibration, thus enhancing smartphone security.

Contribution

This paper introduces EmgAuth, a new EMG-based unlocking method utilizing Siamese networks and data augmentation to improve robustness and eliminate calibration needs.

Findings

Average true acceptance rate of 91.81%

Average false acceptance rate of 7.43%

Effective across different smartphone sizes and scenarios

Abstract

Screen lock is a critical security feature for smartphones to prevent unauthorized access. Although various screen unlocking technologies, including fingerprint and facial recognition, have been widely adopted, they still have some limitations. For example, fingerprints can be stolen by special material stickers and facial recognition systems can be cheated by 3D-printed head models. In this paper, we propose EmgAuth, a novel electromyography(EMG)-based smartphone unlocking system based on the Siamese network. EmgAuth enables users to unlock their smartphones by leveraging the EMG data of the smartphone users collected from Myo armbands. When training the Siamese network, we design a special data augmentation technique to make the system resilient to the rotation of the armband, which makes EmgAuth free of calibration. We conduct extensive experiments including 53 participants and the evaluation results verify that EmgAuth can effectively authenticate users with an average true acceptance rate of 91.81% while keeping the average false acceptance rate of 7.43%. In addition, we also demonstrate that EmgAuth can work well for smartphones with different screen sizes and for different scenarios when users are placing smartphones at different locations and with different orientations. EmgAuth shows great promise to serve as a good supplement for existing screen unlocking systems to improve the safety of smartphones.