Enhanced user verification in IoT applications: a fusion-based multimodal cancelable biometric system with ECG and PPG signals
Author:
Publisher
Springer Science and Business Media LLC
Subject
Artificial Intelligence,Software
Link
https://link.springer.com/content/pdf/10.1007/s00521-023-09394-z.pdf
Reference44 articles.
1. El-Banby GM, Elazm LAA, El-Shafai W et al (2023) Security enhancement of the access control scheme in IoMT applications based on fuzzy logic processing and lightweight encryption. Complex Intel Syst. https://doi.org/10.1007/s40747-023-01149-6
2. Sakr AS, Pławiak P, Tadeusiewicz R, Hammad M (2022) Cancelable ECG biometric based on combination of deep transfer learning with DNA and amino acid approaches for human authentication. Inf Sci 585:127–143. https://doi.org/10.1016/j.ins.2021.11.066
3. Patel VM, Ratha NK, Chellappa R (2015) Cancelable biometrics: a review. IEEE Signal Process Mag 32:54–65. https://doi.org/10.1109/MSP.2015.2434151
4. Rui Z, Yan Z (2019) A survey on biometric authentication: toward secure and privacy-preserving identification. IEEE Access 7:5994–6009. https://doi.org/10.1109/ACCESS.2018.2889996
5. Israel SA, Irvine JM, Cheng A et al (2005) ECG to identify individuals. Pattern Recogn 38:133–142. https://doi.org/10.1016/j.patcog.2004.05.014
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