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An Assessment Method and Toolkit to Evaluate Keyboard Design on Smartphones

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Touch-based interaction dataset for user behavioral analysis in mobile devices.

Daniel Garabato¹, Mario Casado¹, Carlos Dafonte¹

¹CIGUS CITIC - Department of Computer Science and Information Technologies, University of A Coruna. Campus de Elvina s/n, 15071, A Coruna, Spain.

|December 24, 2025

Summary

This summary is machine-generated.

This study introduces a new dataset for mobile device authentication using behavioral biometrics. It captures touch gestures from 37 users to enable research into unique interaction patterns for enhanced security.

Keywords:

Authentication Biometrics Mobile interaction Touch-based gestures

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Area of Science:

Computer Science
Human-Computer Interaction

Background:

Mobile device security is crucial due to increasing integration into daily life.
Current biometric methods like facial recognition and fingerprint scanning have limitations for on-demand authentication.
Behavioral biometrics offer a non-disruptive alternative for user verification through interaction patterns.

Purpose of the Study:

To introduce and describe a novel dataset of touch-based interactions for mobile device authentication.
To facilitate research in behavioral biometrics by providing raw data and feature extraction code.
To support the development of advanced user authentication systems.

Main Methods:

Collected touch-based interaction data from 37 distinct users in a controlled authentication scenario.
Recorded a variety of touch gestures, including single-touch (tap, swipe, pan) and multi-touch (pinch, rotate) events.
Described the data acquisition process and extracted features for analysis.

Main Results:

A comprehensive dataset of touch interactions from 37 users was created.
The dataset includes detailed descriptions of data collection and feature extraction methods.
Base code for handling raw data and extracting features is provided.

Conclusions:

The released dataset and code can advance research in behavioral biometrics for mobile security.
This resource enables researchers to develop and test new authentication methods based on user interaction patterns.
Facilitates further exploration of touch-based behavioral biometrics for secure and seamless user authentication.