Adaptation of the idea of concept drift to some behavioral biometrics: Preliminary studies

Porwik, Piotr; Doroz, Rafał

doi:10.1016/j.engappai.2020.104135

Cited by 5 publications

(2 citation statements)

References 22 publications

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“…Therefore, the reliability of the responses can be enhanced. Similarly, the sample size of the study is based on the following calculation that 530 respondents are a good fit for further study [ 66 ]: where: n number of sample size. σ standard deviation as considered at 1.2 based on prior studies.…”

Section: Methodsmentioning

confidence: 99%

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Analytical study on users’ awareness and acceptability towards adoption of multimodal biometrics (MMB) mechanism in online transactions: a two-stage SEM-ANN approach

Purohit

Dadhich

Ajmera

2022

Multimed Tools Appl

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s The study analyses user awareness of multimodal biometrics and its acceptability for online transactions in the current dynamic world. The study was performed on the five underlying perspectives: User Acceptability, Cognizant Factors towards Biometrics, Technological factors, Perceptional Factors (Fingerprints, Iris, Face Recognition and Voice) and Data Privacy Factors. A questionnaire was prepared and circulated to the 530 biometrics users; on that basis, the corresponding answer was obtained for analysis. SEM is first employed to gauge the research model and test the prominent hypothesized predictors, which are then used as inputs in the neural network to evaluate the relative significance of each predictor variable. By considering the standardized significance of the feed-for-back-propagation of ANN algorithms, the study found a significant effect of DPF_3 (93%), DPF_2 (50%) and DPF_4 (34%) on the adoption of MMB. In the Perceptional construct, PRF_2 (49%) and PRF_3 (33%) was relatively the most important predictor, whereas, in User Acceptability, UAC_2 (37%), UAC_3 & UAC_5 (41%) was vital to be considered. Only one item, TCF_2 (35%), from Technological Factors, followed by Cognizant factors, i.e., CFG_1 (33%), confirmed the best fit model to adopt MMB. The research is a novel effort when compared to past studies as it considered cognizant and perceptual factors in the proposed model, thereby expanding the analytical outlook of MMB literature. Thus, the study also explored several new and valuable practical implications for adopting multimodal instruments of biometrics along with certain limitations.

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Section: Methodsmentioning

confidence: 99%

Section: Survey Instruments and Data Collectionmentioning

confidence: 99%

Analytical study on users’ awareness and acceptability towards adoption of multimodal biometrics (MMB) mechanism in online transactions: a two-stage SEM-ANN approach

Purohit

Dadhich

Ajmera

2022

Multimed Tools Appl

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TypeFormer: transformers for mobile keystroke biometrics

Stragapede,

Delgado-Santos,

Tolosana

et al. 2024

Neural Comput & Applic

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The broad usage of mobile devices nowadays, the sensitiveness of the information contained in them, and the shortcomings of current mobile user authentication methods are calling for novel, secure, and unobtrusive solutions to verify the users’ identity. In this article, we propose TypeFormer, a novel transformer architecture to model free-text keystroke dynamics performed on mobile devices for the purpose of user authentication. The proposed model consists in temporal and channel modules enclosing two long short-term memory recurrent layers, Gaussian range encoding, a multi-head self-attention mechanism, and a block-recurrent transformer layer. Experimenting on one of the largest public databases to date, the Aalto mobile keystroke database, TypeFormer outperforms current state-of-the-art systems achieving equal error rate values of 3.25% using only five enrolment sessions of 50 keystrokes each. In such way, we contribute to reducing the traditional performance gap of the challenging mobile free-text scenario with respect to its desktop and fixed-text counterparts. To highlight the design rationale, an analysis of the experimental results of the different modules implemented in the development of TypeFormer is carried out. Additionally, we analyse the behaviour of the model with different experimental configurations such as the length of the keystroke sequences and the amount of enrolment sessions, showing margin for improvement.

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Concept drift detection based on decision distribution in inconsistent information system

Jin,

Feng,

2023

Knowledge-Based Systems

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Adaptation of the idea of concept drift to some behavioral biometrics: Preliminary studies

Cited by 5 publications

References 22 publications

Analytical study on users’ awareness and acceptability towards adoption of multimodal biometrics (MMB) mechanism in online transactions: a two-stage SEM-ANN approach

Analytical study on users’ awareness and acceptability towards adoption of multimodal biometrics (MMB) mechanism in online transactions: a two-stage SEM-ANN approach

TypeFormer: transformers for mobile keystroke biometrics

Concept drift detection based on decision distribution in inconsistent information system

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