DeepKey: An EEG and Gait Based Dual-Authentication System

TL;DR

Deepkey is a multimodal biometric authentication system combining EEG and gait signals, designed to enhance security against spoofing, with promising real-world deployment results showing low false acceptance and rejection rates.

Contribution

The paper introduces Deepkey, a novel dual-authentication system using EEG and gait signals with an attention-based RNN, improving security and robustness over traditional biometric methods.

Findings

Achieves FAR of 0% and FRR of 1.0% in experiments

Demonstrates technical feasibility in real-world deployment

Outperforms existing biometric authentication methods

Abstract

Biometric authentication involves various technologies to identify individuals by exploiting their unique, measurable physiological and behavioral characteristics. However, traditional biometric authentication systems (e.g., face recognition, iris, retina, voice, and fingerprint) are facing an increasing risk of being tricked by biometric tools such as anti-surveillance masks, contact lenses, vocoder, or fingerprint films. In this paper, we design a multimodal biometric authentication system named Deepkey, which uses both Electroencephalography (EEG) and gait signals to better protect against such risk. Deepkey consists of two key components: an Invalid ID Filter Model to block unauthorized subjects and an identification model based on attention-based Recurrent Neural Network (RNN) to identify a subject`s EEG IDs and gait IDs in parallel. The subject can only be granted access while all the components produce consistent evidence to match the user`s proclaimed identity. We implement Deepkey with a live deployment in our university and conduct extensive empirical experiments to study its technical feasibility in practice. DeepKey achieves the False Acceptance Rate (FAR) and the False Rejection Rate (FRR) of 0 and 1.0%, respectively. The preliminary results demonstrate that Deepkey is feasible, show consistent superior performance compared to a set of methods, and has the potential to be applied to the authentication deployment in real world settings.