Secure vein biometrics authentication based on multimodal artificial template and cryptographic salts
Sarika Khandelwalsarikakhandelwal@gmail.comDepartment of Computer Science and Engineering G H Raisoni College of EngineeringNagpur, Maharashtra, 440016, IndiaView full profile → , Khyati Ramidrkhyatirami@gmail.comSAL Institute of Technology and Engineering Research Gujarat Technological UniversityAhmedabad, Gujarat, 380060, IndiaView full profile → , Harsha Vyawahareharsha.vyawahare@gmail.comDepartment of Computer Science and Engineering Sipna College of Engineering & TechnologyAmravati, Maharashtra, 444701, IndiaView full profile → , Alok Singh Gahlotaloksg@gmail.comDepartment of Computer Science and Engineering MBM UniversityJodhpur, Rajasthan, 342011, IndiaView full profile → , Ruchi Vyasruchivyas85@gmail.comDepartment of Computer Science and Engineering Geetanjali Institute of Technical StudiesUdaipur, Rajasthan, 313022, IndiaView full profile → , *Gaurav KumawatCorresponding authorgaurav.kumawat@jaipur.manipal.eduDepartment of Data Science and Engineering Manipal University JaipurJaipur, Rajasthan, 303007, IndiaView full profile →
* Corresponding author · click or hover a name for details
- Received:
- 07 Jan 2025
- Published Online:
- 08 Dec 2025
- Article type:
- Original Articles
- Language:
- EN
- Article no.:
- JDMSC-2437
- Pages:
- 2915–2931
Abstract
Keywords
Subject Classifications
References
[1] U. Uludag, S. Pankanti, S. Prabhakar, and A. Jain, “Biometric cryptosystems: Issues and challenges,” Proceedings of the IEEE, vol. 92, no. 6, pp. 948–960 (2004), doi: 10.1109/JPROC.2004.827372.
[2] L. Leng, A. B. J. Teoh, L. Leng, M. Li, L. Leng, M. Li, and M. K. Khan, “Orientation range for transposition according to the correlation analysis of 2DPALMHash Code,” in Proc. Int. Symp. Biometrics and Security Technologies (ISBAST), pp. 230–234 (2013), doi: 10.1109/ISBAST.2013.40.
[3] P. P. Paul and M. Gavrilova, “Rank level fusion of multimodal cancelable biometrics,” in Proc. IEEE 13th Int. Conf. Cognitive Informatics and Cognitive Computing (ICCI-CC), pp. 80–87 (2014), doi: 10.1109/ICCI-CC.2014.6921445.
[4] H. Kaur and P. Khanna, “Random distance method for generating unimodal and multimodal cancelable biometric features,” IEEE Transactions on Information Forensics and Security, vol. 14, no. 3, pp. 709–719 (2019).
[5] Z. Liu and S. Song, “An embedded real-time finger-vein recognition system for mobile devices,” IEEE Transactions on Consumer Electronics, vol. 58, no. 2, pp. 522–527 (2012).
[6] J. Galbally, R. Cappelli, A. Lumini, G. Gonzalez-de-Rivera, D. Maltoni, J. Fierrez, J. Ortega-Garcia, and D. Maio, “An evaluation of direct attacks using fake fingers generated from ISO templates,” Pattern Recognition Letters, vol. 31, no. 8, pp. 725–732 (2010).
[7] M. Gomez-Barrero, J. Galbally, C. Rathgeb, and C. Busch, “General framework to evaluate unlinkability in biometric template protection systems,” IEEE Transactions on Information Forensics and Security, vol. 13, no. 6, pp. 1406–1420 (2018).
[8] M. Gomez-Barrero, E. Maiorana, J. Galbally, P. Campisi, and J. Fierrez, “Multi-biometric template protection based on homomorphic encryption,” Pattern Recognition, vol. 67, pp. 149–163 (2017).
[9] D. Maltoni, J. Feng, A. K. Jain, and D. Maio, Handbook of Fingerprint Recognition, Springer International Publishing (2022). [Online]. Available: http://www.siscocorp.com/docs/Privaris_plusID.pdf
[10] S. S. Khandelwal and P. C. Gupta, “Multitier biometric template security using cryptographic salts and personal image identification,” ELCVIA Electronic Letters on Computer Vision and Image Analysis, vol. 13, no. 3 (2014).
[11] A. Agarwal, S. Maheshwari, and G. Yadav, “Vein biometric security using irreversible curve fitting accounting for minimum storage,” in Proc. Int. Conf. Signal Propagation and Computer Technology (ICSPCT), pp. 179–183 (2014).
[12] Vein Dataset, Poznan University of Technology. [Online]. Available: http://biometrics.put.poznan.pl/vein-dataset/
[13] PolyU Finger Vein Database, Hong Kong Polytechnic University, version 1.0 (2017). [Online]. Available: http://www4.comp.polyu.edu.hk/~csajaykr/fvdatabase.htm
[14] S. Bharathi, R. Sudhakar, and V. E. Balas, “Hand vein-based multimodal biometric recognition,” Acta Polytechnica Hungarica, vol. 12, no. 6, pp. 213–229 (2015).
[15] R. Raghavendra, K. B. Raja, J. Surbiryala, and C. Busch, “A low-cost multimodal biometric sensor to capture finger vein and fingerprint,” in Proc. IEEE Int. Joint Conf. Biometrics, pp. 1–7 (2014).
[16] M. I. Gofman, S. Mitra, T.-H. K. Cheng, and N. T. Smith, “Multi-modal biometrics for enhanced mobile device security,” Communications of the ACM, vol. 59, no. 4, pp. 58–65 (2016).
[17] C.-L. Lin and K.-C. Fan, “Biometric verification using thermal images of palm-dorsa vein patterns,” IEEE Transactions on Circuits and Systems for Video Technology, vol. 14, no. 2, pp. 199–213 (2004).
[18] A. Kumar and K. V. Prathyusha, “Personal authentication using hand vein triangulation and knuckle shape,” IEEE Transactions on Image Processing, vol. 18, no. 9, pp. 2127–2136 (2009).
[19] R. Raghavendra, M. Imran, A. Rao, and G. H. Kumar, “Multimodal biometrics: Analysis of hand vein and palm print combination used for person verification,” in Proc. 3rd Int. Conf. Emerging Trends in Engineering and Technology, pp. 526–530 (2010).
[20] M. A. Ferrer, A. Morales, C. M. Travieso, and J. B. Alonso, “Combining hand biometric traits for personal identification,” in Proc. 43rd Annu. Int. Carnahan Conf. Security Technology, pp. 155–159 (2009).
[21] A. Yüksel, L. Akarun, and B. Sankur, “Biometric identification through hand vein patterns,” in Proc. Int. Workshop on Emerging Techniques and Challenges for Hand-Based Biometrics, pp. 1–6 (2010).
[22] G. Kumawat, S. K. Vishwakarma, and P. Chakrabarti, “Cervical cancer prediction using machine learning techniques,” in Proc. Int. Conf. WorldS4, Singapore: Springer Nature Singapore (2023).
[23] Siswanto and S. M. Al-Maghribi, “Solving the eigenproblems of triangular and diagonal strictly double ℝ-astic matrices over min-plus algebra,” Journal of Discrete Mathematical Sciences and Cryptography, vol. 28, no. 6, pp. 2237–2245 (2025), doi: 10.47974/JDMSC-2188.
[24] V. R. Bolla, B. Vikas, S. Potluri, Y. Subbarayudu, G. Sucharitha, and N. Narisetty, “The scalable cloud-based reinforcement learning for multimedia data in cognitive neuroscience for secure healthcare analysis,” Journal of Information and Optimization Sciences, vol. 46, no. 6, pp. 1793–1801 (2025), doi: 10.47974/JIOS-2008.
[25] M. S. Basha, K. R. Prasad, S. K. Mouleeswaran, R. C. Poonia, and S. Sebastian, “Multi-disease detection system with X-ray images using deep learning techniques,” Journal of Information and Optimization Sciences, vol. 45, no. 5, pp. 1379–1388 (2024), doi: 10.47974/JIOS-1710.
[26] S. Jain, N. Rajpal, and P. K. Soni, “Multiple sclerosis detection from brain MRI images using least square-SVM,” Journal of Information and Optimization Sciences, vol. 45, no. 4, pp. 969–980 (2024), doi: 10.47974/JIOS-1620.




