Abstract
This chapter presents literature review in context to existing works with an aim of identifying the present state of research in this domain. This chapter also presents background information regarding biometric watermarking technique and compressive sensing (CS) theory-based encryption technique. The multibiometric watermarking technique is one of the types of biometric watermarking technique. This chapter described application of CS theory in information security field.
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References
Agrawal, M. (2007). Design approaches for multimodal biometric system. M. Tech. thesis, Department of Computer Science and Engineering, IIT, Kanpur.
Ahmed, J., Khan, M., Hwang, S., & Khan, J. (2016). A compression sensing and noise-tolerant image encryption scheme based on chaotic maps and orthogonal matrices. Neural Computing and Applications, 2016, 1–5.
Ashbourn, J. (2014). Biometrics in the new world: The cloud, mobile technology and pervasive identity. Cham: Springer.
Baraniuk, R. (2007). Compressive sensing. IEEE Signal Processing Magazine, 24, 118–124.
Bazargani, M., Ebrahimi, H., & Dianat, R. (2012). Digital image watermarking in wavelet, contourlet and curvelet domains. Journal of Basic and Applied Scientific Research, 2(11), 11296–11308.
Bedi, P., Bansal, R., & Sehgal, P. (2011). Using PSO in image hiding scheme based on LSB substitution. Advances in Computing and Communications, 2011: 259–268.
Bedi, P., Bansal, R., & Sehgal, P. (2012). Multimodal biometric authentication using PSO based watermarking. Procedia Technology, 4, 612–618.
Behaviometics. (2009). Measuring FAR/FRR/EER in continuous authentication. A Technical White Paper, BehavioSec.
Behera, B., & Govindan, V. (2013). Improved multimodal biometric watermarking in authentication systems based on DCT and phase congruency model. International Journal of Computer Science and Network, 2(3), 123–129.
Bhatnagar, G., & Raman, B. (2009). A new robust reference watermarking scheme based on DWT-SVD. Computer Standards & Interfaces, 31, 1002–1013.
Biometrics and Standards. (2009). ITU-T Technology Watch Report, December. Available http://www.itu.int/dms_pub/itu-t/oth/23/01/T230100000D0002MSWE.doc
Biometrics Testing and Statistics. (2006). National Science and Technology Council (NSTC) Report. Available www.biometrics.gov/documents/biotestingandstats.pdf
Candes, E. (2006). Compressive sampling. Proceedings of the International Congress of Mathematicians. pp. 1–20.
Candes, E., & Romberg, J. (2005). L1-Magic: Recovery of Sparse signals via convex programming. pp. 1–19.
Cao, Y., Gong, W., Cao, M., & Bai, S. (2010). Robust biometric watermarking based on contourlet transform for fingerprint and face protection. Proceedings of 2010 I.E. International Symposium on Intelligent Signal Processing and Communication Systems (ISPACS), pp. 1–4.
Chan, C., & Cheng, L. (2004). Hiding data in images by simple LSB substitution. Pattern Recognition, 37, 469–474.
Chaudhary, N., Singh, D., & Hussain, D. (2013). Enhancing security of multimodal biometric authentication system by implementing watermarking utilizing DWT and DCT. IOSR Journal of Computer Engineering, 15(1), 6–11.
Chen, T., Zhang, M., Wu, J., Yuen, C., & Tong, Y. (2016). Image encryption and compression based on kronecker compressed sensing and elementary cellular automata scrambling. Optics & Laser Technology, 84, 118–133.
Cox, I., Kilian, J., Shamoon, T., & Leighton, F. (1997). Secure spread spectrum watermarking for multimedia. IEEE Transactions on Image Processing, 6(12), 1673–1687.
Dai, W., & Milenkovic, O. (2009). Subspace pursuit for compressive sensing signal reconstruction. IEEE Transactions on Information Theory, 55(5), 2230–2249.
Deng, J., Zhao, S., Wang, Y., Wang, L., Wang, H., & Sha, H. (2017). Image compression – Encryption scheme combining 2D compressive sensing with discrete fractional random transform. Multimedia Tools and Applications, 76(7), 10097–10117.
Dili, R., & Mwangi, E. (2007). An image watermarking method based on the singular value transformation and the wavelet transformation. Proceedings of IEEE AFRICON, pp. 1–5.
Donoho, D. (2006). Compressed sensing. IEEE Transaction on Information Theory, 52(4), 1289–1306.
Duarte, M., & Eldar, Y. (2011). Structured compressed sensing: From theory to applications. IEEE Transactions on Signal Processing, 59(9), 4053–4085.
Edward, S., Sumanthi, S., & Ranihemamalini, R. (2011). Person authentication using multimodal biometrics with watermarking. Proceedings of 2011 International Conference on Signal Processing, Communication, Computing and Networking Technologies (ICSCCN), pp. 100–104.
Fakhr, M. (2012). Robust watermarking using compressed sensing framework with application to MP3 audio. The International Journal of Multimedia & Its Applications (IJMA), 4(6), 27–43.
Fernandez, F., Fierrez, J., & Garcia, J. (2012). Quality measures in biometric systems. IEEE Security and Privacy, 52–62.
Fira, M. (2015). Applications of compressed sensing: Compression and encryption. 2015 E-Health and Bioengineering Conference (EHB): 1–4.
Ganic, E. and Eskicioglu, A. (2004). Secure DWT-SVD Domain image watermarking: Embedding data in all frequencies. ACM Multimedia and Security Workshop 2004, Magdeburg, Germany, pp. 1–9.
Gayathri, D., & Rani, R. (2013). Multimodal biometric system: An overview. International Journal of Advanced Research in Computer and Communication Engineering, 2(1), 898–902.
Giannoula, A. and Hatzinakos, D. (2004). Data hiding for multimodal biometric recognition. Proceedings of the 2004 I.E. International Symposium on Circuits and Systems 2, 160–165.
Gilbert, A., Strauss, M., Tropp, J., & Vershynin, R. (2007). One sketch for all: Fast algorithms for compressed sensing. 39th ACM Symposium on Theory of Computing (STOC). pp. 237–246.
Giot, R., El-Abed, M., & Rosenberger, C. (2012). Fast computation of the performance evaluation of biometric systems: Application to multibiometrics. Future Generation Computer Systems, 1, 1–30.
Gonzales, R., & Woods, R. (2002). Digital image processing (pp. 222–226). Upper Saddle River: Prentice Hall, Inc..
Gupta, A., & Raval, M. (2012). A robust and secure watermarking scheme based on singular value replacement. Sadhana © Indian Academy of Science, 37(4), 425–440.
Hajjara, S., Abdallah, M., & Hudaib, A. (2009). Digital image watermarking using localized biorthogonal wavelets. European Journal of Scientific Research, 26(4), 594–608.
Harinda, E., & Natgwirumugara, E. (2015). Security & privacy implications in the placement of biometric-based ID card for Rwanda Universities. Journal of Information Security, 6, 93–100.
Hoang, T., Dat, T., & Sharma, D. (2008). Remote multimodal biometric authentication using bit priority-based fragile watermarking. Proceedings of 19th IEEE International Conference on Pattern Recognition (ICPR 2008), pp. 1–4.
Huang, R., Rhee, K., & Uchida, S. (2014). A parallel image encryption method based on compressive sensing. Multimedia Tools and Applications, 72(1), 71–93.
Inamdar, V., & Rege, P. (2012). Face features based biometric watermarking of digital image using singular value decomposition for fingerprinting. International Journal of Security and Its Applications, 6(2), 47–60.
Inamdar, V., & Rege, P. (2014). Dual watermarking technique with multiple biometric watermarks. Sadhana © Indian Academy of Science, 29(1), 3–26.
Inamdar, V., Rege, P., & Arya, M. (2010). Offline handwritten signature based blind biometric watermarking and authentication technique using biorthogonal wavelet transform. International Journal of Computer Applications, 11(1), 19–27.
Isa, M., & Aljareh, S. (2012). Biometric image protection based on discrete cosine transform watermarking technique. Proceeding of International Conference on Engineering and Technology (ICET), pp. 1–5.
Jahan, R. (2013). Efficient and secure digital image watermarking scheme using DWT-SVD and optimized genetic algorithm based chaotic encryption. International Journal of Science, Engineering and Technology Research (IJSETR), 2(10), 1943–1946.
Jain, A., & Kumar, A. (2012). Biometric recognition: An overview. In E. Mordini & D. Tzovaras (Eds.), Second Generation Biometrics: The Ethical, Legal and Social Context (pp. 49–79). Dordrecht: Springer.
Jain, A., & Nandakumar, K. (2012). Biometric authentication: System security and user privacy. IEEE Computer Society, 45, 87–92.
Jain, A., Prabhakar, S., & Pankanti, S. (1999). A Filterbank based representation for classification and matching of fingerprint. International Joint Conference on Neural Networks (IJCNN), Washington, DC, July, pp. 3284–3285.
Jain, A., Ross, A., & Prabhakar, S. (2004). An introduction to biometric recognition. IEEE Transactions on Circuits and Systems for Video Technology, Special Issue on Image and Video Based Biometrics, 14(1), 4–20.
Jain, A., Ross, A., & Pankanti, S. (2006). Biometrics: A tool for information security. IEEE Transactions on Information Forensics and Security, 1(2), 125–143.
Jain, A., Nandakumar, K., & Nagar, A. (2008). Biometric template security. EURASIP Journal on Advances in Signal Processing, Special Issue on Advanced Signal Processing and Pattern Recognition Methods for Biometrics, January, pp. 1–17.
Javed, A., Fasihullah, M., Munir, M., Usman, I., Shafique, M., Bashir, T., & Khan, M. (2013). A new additive watermarking technique for multimodal biometric identification. Journal of Basic and Applied Scientific Research, 3(7), 935–942.
Joshi, M., Joshi, V., & Raval, M. (2011). Multilevel semi-fragile watermarking technique for improving biometric fingerprint system security. In A. Agrawal, R. C. Tripathi, E. Y.-L. Do, & M. D. Tiwari (Eds.), Intelligent interactive technologies and multimedia (pp. 272–283). Berlin/Heidelberg: Springer.
Joshi, V., Raval, M., Rege, P., & Parulkar, S. (2013). Multistage VQ based exact authentication for biometric images. Computer Society of India (CSI) Journal of Computing, 2(1–2), R3-25–R3-29.
Jundale, V., & Patil, S. (2010). Biometric speech watermarking technique in images using wavelet transform. IOSR Journal of Electronics and Communication Engineering (IOSR-JECE), pp. 33–39.
Kaur, M., Girdhar, A., & Kaur, M. (2010). Multimodal biometric system using speech and signature modalities. International Journal of Computer Applications, 5(12), 13–16.
Kim, W., & Lee, H. (2009). Multimodal biometric image watermarking using two stage integrity verification. Signal Process, 89(12), 2385–2399.
Ko, T. (2005). Multimodal biometric identification for large user population using fingerprint, face and iris recognition. Proceeding of the IEEE 34th Applied Imagery and Pattern Recognition Workshop (AIPR05).
Kolan, H., & Thapaliya, T. (2011). Biometric passport: Security and privacy aspects of machine readable travel document. Available https://diuf.unifr.ch/main/is/sites/diuf.unifr.ch.main.is/files/documents/student-projects/eGov_2011_Hesam_Kolahan_$_Tejendra_Thapaliya.pdf
Kothari, A. (2013). Design, implementation and performance analysis of digital watermarking for video. Ph.D. thesis, JJTU, India.
Kutter, M., & Petitcolas, F. (1999). A fair benchmark for image watermarking systems. Electronic Imaging’ 99. Security and Watermarking of Multimedia Contents, 3657, 1–14.
Langelaar, G., Setyawan, I., & Lagnedijk, R. (2000). Watermarking of digital image and video data – A state of art review. IEEE Signal Processing Magazine, 20–46.
Laska, J., Davenport, M., & Baraniuk, R. (2009). Exact signal recovery from sparsely corrupted measurements through the pursuit of justice. Asilomar Conference on Signals, Systems and Computers, pp. 1556–1560.
Li, C., Ma, B., Wang, Y., & Zhang, Z. (2010). Protecting biometric templates using authentication watermarking, PCM 2010, Part I, LNCS 6297 (pp. 709–718). Berlin/Heidelberg: Springer.
Li, C., Ma, B., Wang, Y., & Zhang, Z. (2011). Sparse reconstruction based watermarking for secure biometric authentication. Biometric Recognition, 7908, 244–251.
Lopez, R., & Boulgouris, N. (2010). Compressive sensing and combinatorial algorithms for image compression. A project report. London: King’s College London.
Lu, J., Plataniotis, N., & Venetsanopoulos, A. (2003). Face recognition using LDA based algorithms. IEEE Transactions on Neural Networks, 14(1), 195–200.
Lupu, E., & Pop, P. (2008). Multimodal biometric systems overview. ACTA Technica Napocensis, 49(3), 39–44.
Ma, B., Li, C., Wang, Y., & Zhang, Z. (2010). Block pyramid based adaptive quantization watermarking for multimodal biometric authentication. Proceedings of 20th IEEE International Conference on Pattern Recognition (ICPR), pp. 1277–1280.
Mansouri, A., Aznaveh, A., & Azar, F. (2009). SVD based digital image watermarking using complex wavelet transform. Sadhana © Indian Academy of Science, 34(3), 393–406.
Mathivadhani, D., & Meena, C. (2010). A comparative study of fingerprint protection using watermarking techniques. Global Journal of Computer Science and Technology, 9(5), 98–102.
Moon, D., Tachae, K., Jung, S., Chung, Y., Moon, K., Ahn, D., & Kim, S. (2005). Performance evaluation of watermarking techniques for secure multimodal biometric systems. Computational Intelligence and Security, pp. 635–642.
Motwani, R. (2010). A Voice-based biometric watermarking scheme for digital rights management of 3D mesh models. Ph.D. thesis, University of Nevada, Reno.
Nagesh, P., Li, B. (2009). Compressive imaging of color images. 2009 I.E. International Conference on Acoustics, Speech and Signal Processing, pp. 1261 – 1264.
Naik, A., & Holambe, R. (2010). Blind DCT Domain digital watermarking for biometric authentication. International Journal of Computer Applications (IJCA), 16(1), 11–15.
Nandakumar, K. (2008). Multibiometric systems: Fusion strategies and template security. Ph.D. thesis, Michigan State University, USA.
Needell, D. (2009). Topics in compressed sensing. Ph.D. thesis, University of California, USA.
Noore, A., Singh, R., Vatsa, M., & Houck, M. (2007a). Enhancing security of fingerprints through contextual biometric watermarking. Forensic Science International, 169(2), 188–194.
Noore, A., Singh, R., Vatsa, M., Houck, M., & Morris, K. (2007b). Robust biometric image watermarking for fingerprint and face template protection. IEICE Electronics Express, 3(2), 23–28.
Panchal, T., & Singh, A. (2013). Multimodal biometric system. International Journal of Advanced Research in Computer Science and Software Engineering, 3(5), 1360–1363.
Pankanti, S. and Yeung, M. (1999). Verification watermarks on fingerprint recognition and retrieval. In Electronic Imaging’99, International Society for Optics and Photonics, pp. 66–78.
Park, K., Jeong, D., Kang, B. and Lee E. (2007). A study on iris feature watermarking on face data. Adaptive and natural computing algorithms, pp. 415–423.
Pato, J., & Millett, L. (2010). Biometric recognition: Challenges and opportunities. Whither Biometric Board. Available http://dataprivacylab.org/TIP/2011sept/Biometric.pdf
Paunwala, M., & Patnaik, S. (2014). Biometric template protection with DCT based watermarking. Machine Vision and Applications, 25(1), 263–275.
Petitcolas, F. (2000). Watermarking schemes evaluation. IEEE Signal Processing Magazine, 17, 58–64.
Picard, J., Vielhauer, C., & Thorwirth, N. (2004). Towards fraud-proof ID documents using multiple data hiding technologies and biometrics. Proceedings of SPIE, 5306, 416–427.
Prabhakar, S. (2001). Fingerprint classification and matching using a filterbank. Ph.D. thesis, Michigan State University, USA.
Qi, M., Lu, Y., Du, N., Wang, C., & Kong, J. (2010). A Novel image hiding approach based on correlation analysis for secure multimodal biometrics. Journal of Network and Computer Applications, 33(3), 247–257.
Ratha, N., Connell, J., & Bolle, R. (2001). Enhancing security and privacy in biometric based authentication systems. IBM Systems Journal, 40(3), 614–634.
Raval, M., & Rege, P. (2003). Discrete wavelet transform based multiple watermarking scheme. Proceedings of the Convergent Technologies for the Asia-Pacific Region, 3, 935–938.
Raval, M., Joshi, M., Rege, P., & Parulkar, S. (2011). Image tampering detection using compressive sensing based watermarking scheme. Proceedings of MVIP, 2011.
Rege, P. (2012). Biometric watermarking. National Seminar on Computer Vision and Image Processing, Rajkot.
Rohani, M., & Avanaki, A. (2009). A watermarking method based on optimizing SSIM index using PSO in DCT domain. CSICC, pp. 418–423.
Ross, A., & Jain A. (2004). Multimodal biometrics: An overview. Proceedings of 12th European Signal Processing Conference (EUSIPCO), pp. 1221–1224.
Sasidhar, K., Kakulapati, V., Ramakrishna, K., & Ka, K. (2010). Multimodal biometric systems – study to improve accuracy and performance. International Journal of Computer Science & Engineering Survey (IJCSES), 1(2), 54–61.
Sheikh, M., & Baraniuk, R. (2007). Blind error free detection of transform domain watermarks. IEEE International Conference on Image Processing, 5, V-453.
Shinfeng, D., Shie, S., & Guo, J. (2010). Improving the robustness of DCT based image watermarking against JPEG compression. Journal of Computer Standards and Interfaces, 32, 60–67.
Sui, Y., Zou, X., & Du, Y. (2013). Cancellable biometrics. In Biometrics: From fiction to practice (pp. 233–252). Singapore: Pan Stanford Publishing Pte. Ltd.
Tagliasacchi, M., Valenzise, G., Tubaro, S., Cancelli, G., & Barni, M. (2009). A compressive sensing based watermarking scheme for sparse image tampering identification. Proceedings of ICIP 2009, pp. 1265–1268.
Tamije Selvy, P., Palanisamy, V., & Elakkiya, S. (2013). A novel watermarking images based on wavelet based contourlet transform energized by biometrics. WSEAS Transactions on Computers, 12(3), 105–115.
Thanki, R., Kher, R., & Vyas, D. (2011). Comparative analysis of digital watermarking techniques. Saarbrücken: LAMBERT Academic Publishing.
Theime, M. (2003). Multimodal biometric systems: Applications and usage scenarios. Arlington: Biometric Consortium Conference.
Tiesheng, F., Guiqiang, L., Chunyi, D., & Danhua, W. (2013). A digital image watermarking method based on the theory of compressed sensing. International Journal Automation and Control Engineering, 2(2), 56–61.
Tropp, J., & Gilbert, A. (2007). Signal recovery from random measurements via orthogonal matching pursuit. IEEE Transactions on Information Theory, 53(12), 4655–4666.
Tsai, H., & Liu, C. (2011). Wavelet based image watermarking with visibility range estimation based on HVS and neural networks. Pattern Recognition, 44, 751–763.
Vatsa, M., Singh, R., Mitra, R., & Noore, A. (2004). Digital watermarking based secure multimodal biometric system. Proceedings of the 2004 I.E. International Conference in Systems Man and Cybernetics, 3, 2983–2987.
Vatsa, M., Singh, R., & Noore, A. (2005). Improving biometric recognition accuracy and robustness using DWT and SVM watermarking. IEICE Electronics Express, 1(12), 362–367.
Vatsa, M., Singh, R., & Noore, A. (2009). Feature based RDWT watermarking for multimodal biometric system. Image and Vision Computing, 27(3), 293–304.
Voloshynovskiy, S., Pereira, S., & Pun, T. (2001). Attacks on digital watermarking: Classification, estimation-based attacks and benchmarks. IEEE Communications Magazine, 118–126.
Wang, Z., & Bovik, A. (2004). A universal image quality index. Journal of IEEE Signal Processing Letters, 9(3), 84–88.
Welling, M. (2005). Fisher linear discriminant analysis. Toronto: Department of Computer Science, University of Toronto.
Wolfgang, R., Podilchdc, C., & Dalp, E. (1999). Perceptual watermarks for digital images and video. Proceedings of IEEE, 87(7), 1108–1126.
Xu, J., Pang, H., & Zhao, J. (2010). Digital image watermarking algorithm based on fast curvelet transform. Journal Software Engineering & Applications, 3, 939–943.
Yang, J., Hua, Y., & William, K. (2000). An efficient LDA algorithm for face recognition. Proceedings of the International Conference on Automation, Robotics and Computer Vision (ICARCV 2000), pp. 34–47.
Zebbiche, K., Khelifi, F., & Bouridane, A. (2008). An efficient watermarking technique for the protection of fingerprint images. EURASIP Journal of Information Security, 1–20.
Zhang, C., Cheng, L., Zhengding, Q., & Cheng, L. (2008). Multipurpose watermarking based on multiscale curvelet transform. IEEE Transactions on Information Forensics and Security, 3(4), 611–619.
Zhang, X., Qian, Z., Ren, Y., & Feng, G. (2011). Watermarking with flexible self-recovery quality based on compressive sensing and compositive reconstruction. IEEE Transactions on Information Forensics and Security, 6(4), 1123–1232.
Zhang, Y., Wong, K., Zhang, L., Wen, W., Zhou, J., & He, X. (2015). exploiting random convolution and random subsampling for image encryption and compression. Signal Processing: Image Communication, 39(20), 202–211.
Zhang, Y., Zhang, L., Zhou, J., Liu, L., Chen, F., & He, X. (2016). A review of compressive sensing in information security field. IEEE Access, 4, 2507–2519.
Zhou, N., Zhang, A., Zheng, F., & Gong, L. (2014). Novel image compression-encryption hybrid algorithm based on key-controlled measurement matrix in compressive sensing. Optics & Laser Technology, 62, 152–160.
Zhou, N., Pan, S., Cheng, S., & Zhou, Z. (2016). Image compression – encryption scheme based on hyper-chaotic system and 2D compressive sensing. Optics & Laser Technology, 82, 121–133.
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Thanki, R.M., Dwivedi, V.J., Borisagar, K.R. (2018). Background Information and Related Works. In: Multibiometric Watermarking with Compressive Sensing Theory. Signals and Communication Technology. Springer, Cham. https://doi.org/10.1007/978-3-319-73183-4_2
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