Hide my Gaze with EOG!: Towards Closed-Eye Gaze Gesture Passwords that Resist Observation-Attacks with Electrooculography in Smart Glasses

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A4 Artikkeli konferenssijulkaisussa

Date

2019-12

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Language

en

Pages

10

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17th International Conference on Advances in Mobile Computing & Multimedia (MoMM2019), pp. 107–116

Abstract

Smart glasses allow for gaze gesture passwords as a hands-free form of mobile authentication. However, pupil movements for password input are easily observed by attackers, who thereby can derive the password. In this paper we investigate closed-eye gaze gesture passwords with EOG sensors in smart glasses. We propose an approach to detect and recognize closed-eye gaze gestures, together with a 7 and 9 character gaze gesture alphabet. Our evaluation indicates good gaze gesture detection rates. However, recognition is challenging specifically for vertical eye movements with 71.2%-86.5% accuracy and better results for opened than closed eyes. We further find that closed-eye gaze gesture passwords are difficult to attack from observations with 0% success rate in our evaluation, while attacks on open eye passwords succeed with 61%. This indicates that closed-eye gaze gesture passwords protect the authentication secret significantly better than their open eye counterparts.

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Keywords

authentication, closed-eye, EOG sensors, hands-free, gaze gestures, mobile, password, smart glasses

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Citation

Findling, R, Quddus, T & Sigg, S 2019, Hide my Gaze with EOG!: Towards Closed-Eye Gaze Gesture Passwords that Resist Observation-Attacks with Electrooculography in Smart Glasses . in 17th International Conference on Advances in Mobile Computing & Multimedia (MoMM2019) . ACM, pp. 107–116, International Conference on Advances in Mobile Computing and Multimedia, Munich, Germany, 02/12/2019 . https://doi.org/10.1145/3365921.3365922