EEG-Driven Biometric Authentication for Investigation of Fourier Synchrosqueezed Transform-ICA Robust Framework

Gorur, Kutlucan; ÖLMEZ, Emre; Ozer, Zeynep; Çetin, Onursal

doi:10.1007/s13369-023-07798-6

Cited by 4 publications

(13 citation statements)

References 60 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The t-distributed stochastic neighbor embedding (t-SNE) was employed to specify the discrimination of each individual on the scattering benchmark for comparison [ 40 ] [ 60 ]. A unique colored cluster represented each subject.…”

Section: Resultsmentioning

confidence: 99%

“…The probability distribution functions (PDFs) of the correlation coefficients between the frontal-lobe electrode locations (Fp1–Fp2 and Fp1–F3) aim to indicate the ability to discriminate among paired subjects. The largest differentiation (the smallest overlap area) means better authentication discrimination, and the smallest differentiation (the largest overlap area) has poor discrimination performances [ 40 ]. According to the PDFs, the lowest discrimination among the cross-subjects and same-subjects was obtained between Subject-1 and Subject-2.…”

Section: Resultsmentioning

confidence: 99%

“…Characterizing EOG time-series responses over the multisite EEG recordings is important for developing more reliable and better performance biometric authentication strategies during signal procedures in a framework [ 40 , 41 ]. Multiple electrodes over the scalp are composed of a multiple mixture of independent sources/electrical signals, which occur from the cerebral and/or extracerebral sources [ 42 ].…”

Section: Methodsmentioning

confidence: 99%

“…In order to calculate the robustness of the biometric authentication systems, the ‘True Acceptance Rate’ (TAR) and ‘False Acceptance Rate’ (FAR) are implemented in the developed biometric approaches. Observation of the quality of specific attempts (genuine or forgery) is carried out to take into account verifying a true identity claim (TAR) and the percentage of unauthorized users (FAR) [ 40 ]. The expected and successful biometric system is designed to maximize the TAR score while minimizing the FAR score during multiple times of attempts.…”

Section: Methodsmentioning

confidence: 99%

“…When the similarity matching ( Sm ) for TAR score is higher than defined th value, the user is treated as genuine else rejected. Otherwise, if the similarity matching ( Sm ) for FAR score is obtained higher than the defined th , the user is treated as an imposter or else rejected [ 40 ]. Threshold levels according to the similarity matching were described as 90% (TAR score) and 80% (FAR score), respectively.…”

Section: Methodsmentioning

confidence: 99%

See 4 more Smart Citations

Fourier Synchrosqueezing Transform-ICA-EMD Framework Based EOG-Biometric Sustainable and Continuous Authentication via Voluntary Eye Blinking Activities

Gorur

2023

Biomimetics

Self Cite

View full text Add to dashboard Cite

In recent years, limited works on EOG (electrooculography)-based biometric authentication systems have been carried out with eye movements or eye blinking activities in the current literature. EOGs have permanent and unique traits that can separate one individual from another. In this work, we have investigated FSST (Fourier Synchrosqueezing Transform)-ICA (Independent Component Analysis)-EMD (Empirical Mode Decomposition) robust framework-based EOG-biometric authentication (one-versus-others verification) performances using ensembled RNN (Recurrent Neural Network) deep models voluntary eye blinkings movements. FSST is implemented to provide accurate and dense temporal-spatial properties of EOGs on the state-of-the-art time-frequency matrix. ICA is a powerful statistical tool to decompose multiple recording electrodes. Finally, EMD is deployed to isolate EOG signals from the EEGs collected from the scalp. As our best knowledge, this is the first research attempt to explore the success of the FSST-ICA-EMD framework on EOG-biometric authentication generated via voluntary eye blinking activities in the limited EOG-related biometric literature. According to the promising results, improved and high recognition accuracies (ACC/Accuracy: ≥99.99% and AUC/Area under the Curve: 0.99) have been achieved in addition to the high TAR (true acceptance rate) scores (≥98%) and low FAR (false acceptance rate) scores (≤3.33%) in seven individuals. On the other hand, authentication and monitoring for online users/students are becoming essential and important tasks due to the increase of the digital world (e-learning, e-banking, or e-government systems) and the COVID-19 pandemic. Especially in order to ensure reliable access, a highly scalable and affordable approach for authenticating the examinee without cheating or monitoring high-data-size video streaming is required in e-learning platforms and online education strategies. Hence, this work may present an approach that offers a sustainable, continuous, and reliable EOG-biometric authentication of digital applications, including e-learning platforms for users/students.

show abstract

Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%