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Related Experiment Video

Updated: Oct 23, 2025

Using Eye Movements Recorded in the Visual World Paradigm to Explore the Online Processing of Spoken Language

Using Eye Movements Recorded in the Visual World Paradigm to Explore the Online Processing of Spoken Language

Published on: October 13, 2018

Differential privacy for eye tracking with temporal correlations.

Efe Bozkir¹, Onur Günlü², Wolfgang Fuhl¹

¹Chair of Human-Computer Interaction, University of Tübingen, Tübingen, Germany.

|August 17, 2021

Summary

This summary is machine-generated.

New privacy techniques for eye tracking in VR/AR glasses improve data security. This research introduces a novel differential privacy method that enhances protection without sacrificing accuracy.

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Last Updated: Oct 23, 2025

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Area of Science:

Human-Computer Interaction
Biometric Security
Computer Vision

Background:

Head-mounted displays (VR/AR) integrate eye tracking for novel interactions.
Eye movement data contains sensitive biometric information, raising privacy concerns.
Existing differential privacy methods struggle with temporal correlations in eye tracking data.

Purpose of the Study:

To develop an advanced differential privacy mechanism tailored for eye movement data.
To address the vulnerability of standard differential privacy to temporal correlations.
To achieve a superior utility-privacy trade-off for eye tracking applications.

Main Methods:

Proposed a novel transform-coding based differential privacy mechanism.
Extended the Fourier perturbation algorithm for eye movement feature data.
Analyzed and compared low-complexity methods for privacy preservation.

Main Results:

Demonstrated significant reductions in sample correlations and query sensitivities.
Achieved a superior utility-privacy trade-off compared to existing methods.
Maintained high classification accuracies with enhanced privacy.

Conclusions:

The proposed transform-coding based differential privacy mechanism offers robust protection for eye tracking data.
This method effectively balances privacy preservation with data utility for VR/AR applications.
Personal identifiers are successfully hidden without compromising essential data accuracy.