Abstract
Biometric authentication systems are nowadays used in a number of sectors such as banking, industrial, and security systems. The biometric templates need to be protected from various attacks which can cause corruption or misuse. Biometric template protection (BTP) holds a vital position in securing the biometric templates at the network as well as at the database. In this paper, we show a potentially fast and invulnerable biometric template protection scheme that makes use of compressed sensing (CS) technique. The proposed system uses total-variation minimization (TV-minimization) based on Nesterov’s algorithm (NESTA). This scheme provides security for the biometric template along with compression. Arnold transformation is used for further improving the security of the template. Finger vein has been used as the biometric template. The experimental results include analysis based on peak-to-peak signal-to-noise ratio between the original and reconstructed finger-vein templates which demonstrate the performance of the system.
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References
Zhou, X., Wolthusen, S., Busch, C., Kuijper, A.: A security analysis of biometric template protection schemes. Image Analysis and Recognition (2009) 429–438
Ashish, M., Sinha, G.: Biometric template protection. J Biostat Biometric App 1(2) (2016) 202
Jain, A.K., Ross, A., Uludag, U.: Biometric template security: Challenges and solutions. In: Signal Processing Conference, 2005 13th European, IEEE (2005) 1–4
Piciucco, E., Maiorana, E., Kauba, C., Uhl, A., Campisi, P.: Cancelable biometrics for finger vein recognition. In: Sensing, Processing and Learning for Intelligent Machines (SPLINE), 2016 First International Workshop on, IEEE (2016) 1–5
Korte, U., Plaga, R.: Cryptographic protection of biometric templates: Chance, challenges and applications. BIOSIG 108 (2007) 33–46
Donoho, D.L.: Compressed sensing. IEEE Transactions on information theory 52(4) (2006) 1289–1306
Candes, E.J., Wakin, M.B.: An introduction to compressive sampling. IEEE signal processing magazine 25(2) (2008) 21–30
Orsdemir, A., Altun, H.O., Sharma, G., Bocko, M.F.: On the security and robustness of encryption via compressed sensing. In: Military Communications Conference, 2008. MILCOM 2008. IEEE, IEEE (2008) 1–7
Rachlin, Y., Baron, D.: The secrecy of compressed sensing measurements. In: Communication, Control, and Computing, 2008 46th Annual Allerton Conference on, IEEE (2008) 813–817
Liu, H., Xiao, D., Zhang, R., Zhang, Y., Bai, S.: Robust and hierarchical water-marking of encrypted images based on compressive sensing. Signal Processing: Image Communication 45 (2016) 41–51
Thanki, R.M., Borisagar, K.R.: Compressive sensing based multiple watermarking technique for biometric template protection. International Journal of Image, Graphics and Signal Processing 7(1) (2014) 53
Thanki, R., Borisagar, K.: Biometric watermarking technique based on cs theory and fast discrete curvelet transform for face and ngerprint protection. In: Advances in Signal Processing and Intelligent Recognition Systems. Springer (2016) 133–144
Zhao, Z., Dong, J., Li, H.: A novel biometric image encryption algorithm based on compressed sensing and dual-tree complex wavelet transform. In: Eighth International Conference on Digital Image Processing (ICDIP 2016), International Society for Optics and Photonics (2016) 100332T–100332T
Nesterov, Y.: Smooth minimization of non-smooth functions. Mathematical programming 103(1) (2005) 127–152
Becker, S., Bobin, J., Candes, E.J.: Nesta: A fast and accurate rst-order method for sparse recovery. SIAM Journal on Imaging Sciences 4(1) (2011) 1–39
Lee, E.C., Lee, H.C., Park, K.R.: Finger vein recognition using minutia-based alignment and local binary pattern-based feature extraction. International Journal of Imaging Systems and Technology 19(3) (2009) 179–186
Yin, Y., Liu, L., Sun, X.: Sdumla-hmt: a multimodal biometric database. In: Chinese Conference on Biometric Recognition, Springer (2011) 260–268
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Surse, N.M., Vinayakray-Jani, P. (2019). Finger-Vein Template Protection Using Compressed Sensing. In: Saini, H., Sayal, R., Govardhan, A., Buyya, R. (eds) Innovations in Computer Science and Engineering. Lecture Notes in Networks and Systems, vol 32. Springer, Singapore. https://doi.org/10.1007/978-981-10-8201-6_34
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DOI: https://doi.org/10.1007/978-981-10-8201-6_34
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