L Yasmeen Abdrabou (Lancaster University), Mariam Hassib (Fortiss Research Institute of the Free State of Bavaria), Shuqin Hu (LMU Munich), Ken Pfeuffer (Aarhus University), Mohamed Khamis (University of Glasgow), Andreas Bulling (University of Stuttgart), Florian Alt (University of the Bundeswehr Munich)

Existing gaze-based methods for user identification either require special-purpose visual stimuli or artificial gaze behaviour. Here, we explore how users can be differentiated by analysing natural gaze behaviour while freely looking at images. Our approach is based on the observation that looking at different images, for example, a picture from your last holiday, induces stronger emotional responses that are reflected in gaze behavioor and, hence, is unique to the person having experienced that situation. We collected gaze data in a remote study (N = 39) where participants looked at three image categories: personal images, other people’s images, and random images from the Internet. We demonstrate the potential of identifying different people using machine learning with an accuracy of 85%. The results pave the way towards a new class of authentication methods solely based on natural human gaze behaviour.

View More Papers

A Cross-Verification Approach with Publicly Available Map for Detecting...

Takami Sato, Ningfei Wang (University of California, Irvine), Yueqiang Cheng (NIO Security Research), Qi Alfred Chen (University of California, Irvine)

Read More

BliMe: Verifiably Secure Outsourced Computation with Hardware-Enforced Taint Tracking

Hossam ElAtali (University of Waterloo), Lachlan J. Gunn (Aalto University), Hans Liljestrand (University of Waterloo), N. Asokan (University of Waterloo, Aalto University)

Read More

Facilitating Threat Modeling by Leveraging Large Language Models

Isra Elsharef, Zhen Zeng (University of Wisconsin-Milwaukee), Zhongshu Gu (IBM Research)

Read More

GNNIC: Finding Long-Lost Sibling Functions with Abstract Similarity

Qiushi Wu (University of Minnesota), Zhongshu Gu (IBM Research), Hani Jamjoom (IBM Research), Kangjie Lu (University of Minnesota)

Read More