Techniques for continuous touch-based authentication
The field of continuous touch-based authentication has been rapidly developing over the last decade, creating a fragmented and difficult-to-navigate area for researchers and application developers alike. In this study, we perform a systematic literature analysis of 30 studies on the techniques used...
| Հիմնական հեղինակներ: | , , |
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| Ձևաչափ: | Conference item |
| Լեզու: | English |
| Հրապարակվել է: |
Springer
2022
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| _version_ | 1826309118212702208 |
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| author | Georgiev, M Eberz, S Martinovic, I |
| author_facet | Georgiev, M Eberz, S Martinovic, I |
| author_sort | Georgiev, M |
| collection | OXFORD |
| description | The field of continuous touch-based authentication has been rapidly developing
over the last decade, creating a fragmented and difficult-to-navigate area for researchers and
application developers alike. In this study, we perform a systematic literature analysis of
30 studies on the techniques used for feature extraction, classification, and aggregation in
continuous touch-based authentication systems as well as the performance metrics reported
by each study. Based on our findings, we design a set of experiments to compare the performance of the most frequently used techniques in the field under clearly defined conditions. In
addition, we introduce two new techniques for continuous touch-based authentication: an expanded feature set (consisting of 149 unique features) and a multi-algorithm ensemble-based
classifier. The comparison includes 13 feature sets, 11 classifiers, and 5 aggregation methods.
In total, 204 model configurations are examined and we show that our novel techniques outperform the current state-of-the-art in each category. The results are also validated across
three different publicly available datasets. Our best performing model achieves 4.8% EER
using 16 consecutive strokes. Finally, we discuss the findings of our investigation with the
aim of making the field more understandable and accessible for researchers and practitioners. |
| first_indexed | 2024-03-07T07:29:25Z |
| format | Conference item |
| id | oxford-uuid:c826f68b-7a03-41f3-b941-27f11ecc07f8 |
| institution | University of Oxford |
| language | English |
| last_indexed | 2024-03-07T07:29:25Z |
| publishDate | 2022 |
| publisher | Springer |
| record_format | dspace |
| spelling | oxford-uuid:c826f68b-7a03-41f3-b941-27f11ecc07f82022-12-16T09:24:17ZTechniques for continuous touch-based authenticationConference itemhttp://purl.org/coar/resource_type/c_5794uuid:c826f68b-7a03-41f3-b941-27f11ecc07f8EnglishSymplectic ElementsSpringer2022Georgiev, MEberz, SMartinovic, IThe field of continuous touch-based authentication has been rapidly developing over the last decade, creating a fragmented and difficult-to-navigate area for researchers and application developers alike. In this study, we perform a systematic literature analysis of 30 studies on the techniques used for feature extraction, classification, and aggregation in continuous touch-based authentication systems as well as the performance metrics reported by each study. Based on our findings, we design a set of experiments to compare the performance of the most frequently used techniques in the field under clearly defined conditions. In addition, we introduce two new techniques for continuous touch-based authentication: an expanded feature set (consisting of 149 unique features) and a multi-algorithm ensemble-based classifier. The comparison includes 13 feature sets, 11 classifiers, and 5 aggregation methods. In total, 204 model configurations are examined and we show that our novel techniques outperform the current state-of-the-art in each category. The results are also validated across three different publicly available datasets. Our best performing model achieves 4.8% EER using 16 consecutive strokes. Finally, we discuss the findings of our investigation with the aim of making the field more understandable and accessible for researchers and practitioners. |
| spellingShingle | Georgiev, M Eberz, S Martinovic, I Techniques for continuous touch-based authentication |
| title | Techniques for continuous touch-based authentication |
| title_full | Techniques for continuous touch-based authentication |
| title_fullStr | Techniques for continuous touch-based authentication |
| title_full_unstemmed | Techniques for continuous touch-based authentication |
| title_short | Techniques for continuous touch-based authentication |
| title_sort | techniques for continuous touch based authentication |
| work_keys_str_mv | AT georgievm techniquesforcontinuoustouchbasedauthentication AT eberzs techniquesforcontinuoustouchbasedauthentication AT martinovici techniquesforcontinuoustouchbasedauthentication |