Multi Biometric Fuzzy Vault Generation Using Chaff Points and Cuckoo Search Optimization

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Usage of human physical and behavioural traits for individual identification dates back to the beginning of human civilization. The demand for automation of biometric system was raised as a result of increase in population. Nowadays, in many applications biometric authentication is gaining popularity. However, its performance is still a constraint for its wide scale implementation. In our proposed work, fingerprint and ear are considered as it provides higher performance than unimodal biometric. Our objective is to store the biometric in the database as fuzzy vault, as storing the biometric template directly in to the database weakens the system security. Initially, the input images of fingerprint and ear are pre-processed to filter the noise and to improve the image contrast. From the pre-processed fingerprint, minutiae points are extracted. Upon the pre-processed ear image, the dimension reducing technique, Principal Component Analysis (PCA), is applied to extract global features. Texture feature is also extracted from both the modalities using Local Gabor XOR Patterns (LGXP). To these extracted features cuckoo optimization is applied to generate optimized points. Chaff points are generated, from randomly generated secret keys. These chaff points are fused with optimized points to generate fuzzy vault. The sensitivity, specificity and accuracy are calculated for the cuckoo optimized fuzzy vault authentication system and compared with the non- optimized fuzzy vault system.

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Chaff Points; Cuckoo Search Optimization; Fuzzy Vault; Local Gabor XOR Patterns; Minutiae Points; Principal Component Analysis; Texture Feature

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R. Bolle, A.K. Jain and S. Pankanti, Biometrics: Personal Identification in Networked Society (Kluwer Academic Publishers, 1999).

Anil Jain, Lin Hong and Sharath Pankati, “Can multi biometrics improve the performance?,” Proc. AutoID`99, Summit, NJ, pp. 59-64, Oct 1999.

Mark Burge and Wilhelm Burger, Ear Biometrics, BIOMETRICS: Personal Identification in a Networked Society, pp.273-286, 1999.

Kevin W. Bowyer and Ping Yan, “Ear Biometrics Using 2D and 3D Images,” IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 29 Issue 8, pp. 1297-1308, August 2007.

S. Deb and X.S. Yang, “Engineering Optimisation by Cuckoo Search,” International Journal Mathematical Modelling and Numerical Optimisation, Vol. 1, No.4, pp: 330-343, 2010.

Beni, G. and Wang, J., “Swarm Intelligence in Cellular Robotic Systems,” Proceed. NATO Advanced Workshop on Robots and Biological Systems, Tuscany, Italy, June 26-30, 1989.

Juels and M. Sudan, “A Fuzzy Vault Scheme,” Proc. IEEE Int’l. Symp. Inf. Theory, A.Lapidoth and E. Teletar, Eds., pp. 408, 2002.

Bhanu B. and Hui Chen, “Shape model-based 3D ear detection from side face range images,” Proc. of the IEEE Conference on Computer Vision and Pattern Recognition CVPR. Washington-DC, USA, 122–127, 2005.

V. Barnabas , K. Bowyer and K. Chang, “Comparison and combination of ear and face images in appearance-based biometrics,” IEEE Transaction on Pattern Analysis and Machine Intelligence., Vol. 25, pp. 1160–1165, 2003.

Price K and Storn R, “Differential evolution—a simple and efficient heuristic for global optimization over continuous spaces,” Journal of Global Optimization 11(4):341–359, 1997.

Juels and M. Wattenberg, “A Fuzzy Commitment Scheme,” G. Tsudik, Ed., Sixth ACM Conf. Computer and Comm. Security, pp. 28-36, 1999.

D. Bleichenbacher and P. Nguyen, “Noisy polynomial interpolation and noisy Chinese remaindering,” B. Preneel, editor, Eurocrypt '00, pp. 53- 69. LNCS no. 1807, 2002.

Erkan Besdok and Pinar Civicioglu, “A conceptual comparison of the Cuckoo-search, particle swarm optimization, differential evolution and artificial bee colony algorithms,” Springer Science+Business Media B.V., Published online 6 July 2011.

S. Deb and X.S. Yang, “Cuckoo search via Lévy flights,” Proc. of World Congress on Nature & Biologically Inspired Computing (NaBIC), India. IEEE Publications, USA, pp: 210-214, December 2009.

Thiyaneswaran, B., Padma, S., Human authorization using wavelet and tensor object analysis of the iris biometrics, (2012) International Review on Computers and Software (IRECOS), 7 (6), pp. 3047-3055.

Aravinth, J., Valarmathy, S., Score-level fusion technique for multi-modal biometric recognition using ABC-based neural network, (2013) International Review on Computers and Software (IRECOS), 8 (8), pp. 1889-1900.

J. Chen, S. Shan and S. Xie ,, “Fusing Local Patterns of Gabor Magnitude and Phase for Face Recognition,” IEEE Transactions On Image Processing, Vol. 19, no. 5, May 2010.

Aydi, W., Masmoudi, N., Kamoun, L., A fast and accurate circular segmentation method for iris recognition systems, (2014) International Review on Computers and Software (IRECOS), 9 (3), pp. 468-477.

Poinsot, A., Yang, F., Palmprint and face score level fusion for contactless small sample biometric recognition and verification, (2010) International Review on Computers and Software (IRECOS), 5 (2), pp. 156-167.

Mercy Geraldine, J., Kirubakaran, E., An efficient technique for frequent item set mining in time series data with aid of AFCM, (2013) International Review on Computers and Software (IRECOS), 8 (12), pp. 2765-2772.

George, G., Parthiban, L., FCM-FCS: Hybridization of fractional cuckoo search with FCM for high dimensional data clustering process, (2013) International Review on Computers and Software (IRECOS), 8 (11), pp. 2576-2585.

Nancharaiah, B., Chandra Mohan, B., On the performance of MANET using QoS protocol, (2013) International Review on Computers and Software (IRECOS), 8 (10), pp. 2356-2362.

Thomas, J., Kulanthaivel, G., Preterm birth prediction using cuckoo search-based fuzzy min-max neural network, (2013) International Review on Computers and Software (IRECOS), 8 (8), pp. 1854-1862.

Moravej, Z., Akhlaghi, A., A new approach for DG allocation in distribution network with time variable loads using cuckoo search, (2012) International Review of Electrical Engineering (IREE), 7 (2), pp. 4027-4034.


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