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FH-SSTNet: Forehead Creases for User Verification with Spatio-Spatial Temporal Network


แนวคิดหลัก
Utilizing 3D spatio-spatial temporal convolution, FH-SSTNet offers superior performance in forehead-based user verification.
บทคัดย่อ
  • Biometric authentication is crucial for secure access control.
  • Forehead creases offer a unique biometric trait for user verification.
  • FH-SSTNet outperforms existing methods in identity authentication using forehead patterns.
  • The model incorporates triplet loss and Arcloss to enhance discrimination capability.
  • Extensive experiments on the FH-V1 dataset demonstrate the effectiveness of FH-SSTNet.
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สถิติ
Experimentation on the FH-V1 dataset shows superior performance of FH-SSTNet compared to ResNet50. Proposed method achieved an EER of 1.77% with TMR and FMR at 1.15% and 0.15%.
คำพูด
"Our proposed algorithm, FH-SSTNet, achieved an EER of 32.73% with TMR and FMR at 1.15% and 0.15%, respectively." "The improved performance of the proposed method can be attributed to the proposed 3D representation in FH-SSTNet."

ข้อมูลเชิงลึกที่สำคัญจาก

by Geetanjali S... ที่ arxiv.org 03-26-2024

https://arxiv.org/pdf/2403.16202.pdf
FH-SSTNet

สอบถามเพิ่มเติม

How can forehead creases as a biometric trait impact user privacy?

Forehead creases, as a unique biometric trait, can have implications for user privacy. Since forehead patterns are distinctive and enduring characteristics, using them for authentication purposes raises concerns about the potential misuse or unauthorized access to this personal data. If not properly secured, the collection and storage of forehead crease information could lead to privacy breaches if accessed by malicious actors. Additionally, there is a risk of individuals being identified without their consent or knowledge based on their forehead patterns, which may infringe upon their right to privacy.

What are the potential limitations or biases associated with using forehead patterns for authentication?

When utilizing forehead patterns for authentication, several limitations and biases need to be considered. One limitation is the variability in how these patterns may change over time due to factors like aging or environmental influences. This variability could result in false rejections during verification if the stored pattern does not match real-time data accurately. Moreover, certain populations may exhibit less distinct or recognizable forehead creases, leading to potential bias in identification accuracy across different demographic groups.

How might advancements in biometric authentication technology influence broader cybersecurity practices?

Advancements in biometric authentication technology have significant implications for broader cybersecurity practices. By incorporating more secure and reliable biometric traits like forehead patterns into verification systems, organizations can enhance their overall security posture against traditional methods such as passwords that are susceptible to hacking and phishing attacks. Biometrics offer an additional layer of protection by providing unique identifiers that are difficult to replicate or steal. Furthermore, improved biometric technologies enable organizations to implement multi-factor authentication strategies that combine various biometric modalities for enhanced security measures. This approach strengthens access control mechanisms and reduces the likelihood of unauthorized access attempts. Overall, advancements in biometric authentication contribute towards establishing robust cybersecurity frameworks by offering efficient identity verification methods that prioritize accuracy and reliability while mitigating common vulnerabilities associated with traditional password-based systems.
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