A Comparison of Authentication Methods via Keystroke Dynamics

Aron Lo, Victor H. Ayma, Juan Gutierrez-Cardenas

    Research output: Chapter in Book/Report/Conference proceedingPaper (Conference contribution)peer-review

    Abstract

    Authentication systems based on keystroke dynamics analyze the typical typing pattern of a user when interacting with an input device, such as the keyboard of a computer. In the literature, three major approaches on keystroke dynamics can be found: distance-based, statistical-based and machine learning-based approaches, which are often used to solve the problem. Nevertheless, in the literature there are several works which results are obtained from different comparison methodologies; this represents a great problem for future researchers who seek to improve or advance with prior works. Furthermore, by using proprietary databases, researchers do not provide a good overview of the overall performance of their methods, but rather an overview in a specific case: That represented by their database. In this investigation, we proposed to evaluate the performance of the most representative classifiers in two of the three most common approaches used in keystroke dynamics using the public Greyc dataset. The experimental results, reveal that machine-learning based approaches outperformed the distance-based techniques. Moreover, the Random Forest classifier, provided encouraging results.

    Original languageEnglish
    Title of host publicationProceedings of the 2020 IEEE Engineering International Research Conference, EIRCON 2020
    PublisherInstitute of Electrical and Electronics Engineers Inc.
    ISBN (Electronic)9781728183671
    DOIs
    StatePublished - 21 Oct 2020
    Event2020 IEEE Engineering International Research Conference, EIRCON 2020 - Lima, Peru
    Duration: 21 Oct 202023 Oct 2020

    Publication series

    NameProceedings of the 2020 IEEE Engineering International Research Conference, EIRCON 2020

    Conference

    Conference2020 IEEE Engineering International Research Conference, EIRCON 2020
    CountryPeru
    CityLima
    Period21/10/2023/10/20

    Keywords

    • Computer Security
    • Keystroke Dynamics
    • Machine Learning
    • User Verification

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