Smartphone Authentication Based on 3D Touch Sensor and Finger Locations on Touchscreens via Decision-Making Techniques

Smartphone authentication systems must balance security and user convenience, which is a persistent challenge in the digital realm. Traditional biometrics, such as fingerprints and facial recognition, face vulnerabilities to spoofing and environmental conditions, limiting reliability. This study introduces a novel approach by integrating three-dimensional (3D) touch sensors with finger location data for authentication. The goal is to develop a system that improves accuracy while minimizing false positives and negatives, leveraging touch pressure and spatial interaction as unique biometric identifiers. Data from 20 participants, including pressure levels, spatial coordinates, and timestamps, were analysed using Random Forest (RF) and Extreme Gradient Boosting (XGBoost) models. The results showed that combining pressure sensitivity with spatial data significantly improved performance, achieving an F1- score of 0.83 and an accuracy of 83%. The system demonstrated balanced precision (0.84) and recall (0.83), effectively reducing false positives and negatives. Robustness was confirmed through cross-validation tests, which validated the consistency across datasets and real-time usability scenarios. This study establishes a foundation for secure, user-friendly smartphone authentication, highlighting the potential of 3D touch technology in addressing current biometric system limitations. This approach opens avenues for further research in mobile security, integrating multimodal biometric data with advanced machine learning techniques. Reason for Expression of Concern:The Editors wish to alert readers to potential concerns regarding the reliability of the findings reported in “Smartphone Authentication Based on 3D Touch Sensor and Finger Locations on Touchscreens via Decision-Making Techniques”. The journal has initiated an additional editorial assessment of the article’s methodology, data provenance, and reported outcomes to confirm their reliability and reproducibility. This notice is issued to ensure transparency while the review is ongoing. The Expression of Concern does not constitute a final determination regarding the validity of the work. The journal will update readers once the assessment is completed and will take any necessary editorial action in accordance with the journal’s policies and COPE guidance.See expression of concern available at:https://doi.org/10.58496/2026/004https://mesopotamian.press/journals/index.php/CyberSecurity/article/view/1028

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Publication Details

Journal
Mesopotamian Journal of CyberSecurity
Published
2025-02-22
DOI
https://doi.org/10.58496/mjcs/2025/011
Citations
1
Primary Topic
User Authentication and Security Systems
Type
article
Field-Weighted Citation Impact
3.25
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article

Smartphone Authentication Based on 3D Touch Sensor and Finger Locations on Touchscreens via Decision-Making Techniques

Maytham M. Hammood, Moceheb Lazam Shuwandy, Rawan A. Alsharida
1 citations
Mesopotamian Journal of CyberSecurity
User Authentication and Security Systems
3.25
article

Smartphone Authentication Based on 3D Touch Sensor and Finger Locations on Touchscreens via Decision-Making Techniques

Maytham M. Hammood, Moceheb Lazam Shuwandy, Rawan A. Alsharida
article en
1 citations

Abstract

Smartphone authentication systems must balance security and user convenience, which is a persistent challenge in the digital realm. Traditional biometrics, such as fingerprints and facial recognition, face vulnerabilities to spoofing and environmental conditions, limiting reliability. This study introduces a novel approach by integrating three-dimensional (3D) touch sensors with finger location data for authentication. The goal is to develop a system that improves accuracy while minimizing false positives and negatives, leveraging touch pressure and spatial interaction as unique biometric identifiers. Data from 20 participants, including pressure levels, spatial coordinates, and timestamps, were analysed using Random Forest (RF) and Extreme Gradient Boosting (XGBoost) models. The results showed that combining pressure sensitivity with spatial data significantly improved performance, achieving an F1- score of 0.83 and an accuracy of 83%. The system demonstrated balanced precision (0.84) and recall (0.83), effectively reducing false positives and negatives. Robustness was confirmed through cross-validation tests, which validated the consistency across datasets and real-time usability scenarios. This study establishes a foundation for secure, user-friendly smartphone authentication, highlighting the potential of 3D touch technology in addressing current biometric system limitations. This approach opens avenues for further research in mobile security, integrating multimodal biometric data with advanced machine learning techniques. Reason for Expression of Concern:The Editors wish to alert readers to potential concerns regarding the reliability of the findings reported in “Smartphone Authentication Based on 3D Touch Sensor and Finger Locations on Touchscreens via Decision-Making Techniques”. The journal has initiated an additional editorial assessment of the article’s methodology, data provenance, and reported outcomes to confirm their reliability and reproducibility. This notice is issued to ensure transparency while the review is ongoing. The Expression of Concern does not constitute a final determination regarding the validity of the work. The journal will update readers once the assessment is completed and will take any necessary editorial action in accordance with the journal’s policies and COPE guidance.See expression of concern available at:https://doi.org/10.58496/2026/004https://mesopotamian.press/journals/index.php/CyberSecurity/article/view/1028

Mesopotamian Journal of CyberSecurityVol. 5(1)
University of Tikrit (IQ)
Openalex Percentile: Top 11%
User Authentication and Security Systems
3.25
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