2022
DOI: 10.1016/j.cose.2022.102716
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Behavioral embedding for continuous user verification in global settings

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Cited by 3 publications
(3 citation statements)
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“…Researchers of [28][29][30] chose other ML classifiers for their models. In study [28], a continuous touch-dynamics authentication method was studied.…”
Section: Literature Reviewmentioning
confidence: 99%
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“…Researchers of [28][29][30] chose other ML classifiers for their models. In study [28], a continuous touch-dynamics authentication method was studied.…”
Section: Literature Reviewmentioning
confidence: 99%
“…RF, KNN, gradient boosting classifier (GBC), and linear SVM (L-SVM) classifiers were evaluated with these data. While RF and GBC had similar accuracy, GBC was chosen as the optimal classifier due to a faster performance with an average accuracy under the ROC curve (AUC) of 0.9692 and a learning time of 117 s. For [29], researchers attempted to create a privacy-preserving global continuous authentication model using touch dynamics. To achieve this, base features would be extracted from initial user sessions.…”
Section: Literature Reviewmentioning
confidence: 99%
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