The Way we Type Reveals our Native Language

Knowing some characteristics of an unknown user is useful information for security and commercial purposes. One of the acquired characteristics is the user's native language, and its recognition can be achieved with data derived from the text he/she types, since text is the most widespread mean...

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Bibliographic Details
Published in:IEEE access 2023-01, Vol.11, p.1-1
Main Authors: Tsimperidis, Ioannis, Grunova, Denitsa, Papakostas, George A.
Format: Article
Language:English
Subjects:
Algorithms
Authentication
Biometrics
Biometrics (access control)
data mining
Feature extraction
Heuristic algorithms
Keyboards
Keystroke dynamics
Machine learning
Machine learning algorithms
native language identification
Natural language processing
Object recognition
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Summary:Knowing some characteristics of an unknown user is useful information for security and commercial purposes. One of the acquired characteristics is the user's native language, and its recognition can be achieved with data derived from the text he/she types, since text is the most widespread means of communication between Internet users. Keystroke dynamics, which leverages data derived from how user types, ensures that no sensitive data are leaked. In this work, data from the daily typing of users of five different native languages are collected, keystroke dynamics features are extracted, the most suitable ones are selected using a feature selection algorithm, well-known machine learning models and a boosting algorithm are used, and a rate of correct prediction that exceeds 90% is achieved. Knowing a user's native language can help strengthen authentication systems, make better use of online services, and protect unsuspecting users from falling victim to fraud.
ISSN:2169-3536
2169-3536
DOI:10.1109/ACCESS.2023.3313510