iProfile: Collecting and Analyzing Keystroke Dynamics from Android Users

Haytham Elmiligi, Sherif Saad

2022

Abstract

Keystroke dynamics is one of the most popular behavioural biometrics that are currently being used as a second factor of authentication for many web services and applications. One of the reasons that makes it really popular is that it is a resettable biometric, which meets one of the main usability requirements of authentication systems. With the recent advances in mobile technologies, developers and researchers utilized several machine learning algorithms to identify smartphone users based on their keystroke dynamics. The biggest problem that faces researchers in this area is the ability to collect datasets from smartphone users that could be used to train the machine learning algorithms and, hence, create accurate predictive model. This paper introduces iProfile, a native Android application that collects keystroke dynamics from Android smartphone users. This application opens the door for researchers to recruit participants from all over the world to contribute to the data collection of keystroke dynamics. Our iProfile application allows researchers to study the impact of several parameters, such as hardware brands, users’ geolocation, native language text direction, and several other factors, on the accuracy of machine learning classifiers. It also helps maintain a standard benchmark for keystroke dynamics. Having a standard benchmark helps researchers better evaluate their work based on consistent data collection procedures and evaluation metrics. This paper explains the main building blocks of the iProfile application, the algorithms used in the implementation, the communication protocol with the database server, the structure and format of the generated dataset and the feature extraction approaches. As a proof of concept, the app was used to develop a novel feature-set that identifies Android users based on 147 features.

Paper Citation

in Harvard Style

Elmiligi H. and Saad S. (2022). iProfile: Collecting and Analyzing Keystroke Dynamics from Android Users. In Proceedings of the 8th International Conference on Information Systems Security and Privacy - Volume 1: ICISSP, ISBN 978-989-758-553-1, pages 621-628. DOI: 10.5220/0011002600003120

in Bibtex Style

@conference{icissp22,
author={Haytham Elmiligi and Sherif Saad},
title={iProfile: Collecting and Analyzing Keystroke Dynamics from Android Users},
booktitle={Proceedings of the 8th International Conference on Information Systems Security and Privacy - Volume 1: ICISSP,},
year={2022},
pages={621-628},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0011002600003120},
isbn={978-989-758-553-1},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 8th International Conference on Information Systems Security and Privacy - Volume 1: ICISSP,
TI - iProfile: Collecting and Analyzing Keystroke Dynamics from Android Users
SN - 978-989-758-553-1
AU - Elmiligi H.
AU - Saad S.
PY - 2022
SP - 621
EP - 628
DO - 10.5220/0011002600003120