Device-based Behavioral Biometrics

Device-Based Behavioral Biometrics is a behavioral biometric modality that uniquely identifies individuals based on their distinctive patterns of interaction with computing devices, such as typing dynamics, touch gestures, or mouse movements, as distinguished from physiological or knowledge-based authentication methods.

25

Publications

1.3K

Citations

64

Authors

40

Institutions

Publications per year

2017–2026

15

Authors

64

  1. SE
    Serge Egelman

    University of California, Berkeley, United States

    2 publications · 134 citations

    2

    h-index

  2. MH
    Marian Harbach

    Leibniz University Hannover, Germany

    2 publications · 134 citations

    2

    h-index

  3. MS
    Mohammad S. Obaidat

    University of Jordan, Jordan

    2 publications · 59 citations

    2

    h-index

  4. AD
    Alexander De Luca

    Ludwig-Maximilians-Universität München, Germany

    2 publications · 134 citations

    2

    h-index

  5. AY
    Artsiom Yautsiukhin

    Institute of Informatics and Telematics, Italy

    1 publications · 47 citations

    1

    h-index

1–5 of 64

Venues

  1. 1

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  2. 1

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  3. Multimedia Tools and Applications

    1 publications · 27 citations

    1

    h-index

  4. IEEE Communications Surveys & Tutorials

    ComST · 1 publications · 215 citations

    1

    h-index

  5. Pattern Recognition

    1 publications · 47 citations

    1

    h-index

1–5