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Experimental Analysis and Verification of a Multi-modal-Biometrics Identity Verification Framework Based on the Dempster-Shafer Theory

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Complex, Intelligent and Software Intensive Systems (CISIS 2022)

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 497))

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Abstract

By extending some previous research contributions, this paper focuses the attention on a state-of-the-art data fusion algorithm for multi-modal biometric identification, which makes use of the Dempster-Shafer (DS) theory for supporting the combination of two different beliefs that can be derived from the algorithm. The specific contributions of this paper are represented by a complete case study that focuses the attention on a reference architecture that supports multi-modal bio-metric identity verification over big data settings, deep overview on state-of-the-art results, and a comprehensive experimental assessment and analysis of the proposed framework.

This research has been made in the context of the Excellence Chair in Computer Engineering at LORIA, University of Lorraine, Nancy, France.

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References

  1. Cuzzocrea, A., Mumolo, E.: Dempster-shafer-based fusion of multi-modal biometrics for supporting identity verification effectively and efficiently. In: 2nd IEEE International Conference on Human-Machine Systems, ICHMS 2021, Proceedings, pp. 1–8 (2021)

    Google Scholar 

  2. Wang, Y., Tan, T., Jain, A.K.: Combining face and iris biometrics for identity verification. In: Proceedings of International Conference on Audio- and Video-Based Biometric Person Authentication, pp. 805–813 (2003)

    Google Scholar 

  3. Ashbourn, J.: Biometrics: Advanced Identity Verification: The Complete Guide. Springer (2014)

    Google Scholar 

  4. Kittler, J., Matas, J., Jonsson, K., Ramos Sánchez, M.U.: Combining evidence in personal identity verification systems. Pattern Recognit. Lett. 18(9), 845–852 (1997)

    Google Scholar 

  5. Xu, J., Cha, M., Heyman, J.L., Venugopalan, S., Abiantun, R., Savvides, M.: Robust local binary pattern feature sets for periocular biometric identification. In: Proceedings of 2010 Fourth IEEE International Conference on Biometrics: Theory, Applications and Systems (BTAS), , pp. 1–8 (2010)

    Google Scholar 

  6. da Costa, D.M.M., dos Santos Passos, H., Peres, S.M., Lima, C.A.M.: A comparative study of feature level fusion strategies for multimodal biometric systems based on face and Iris. In: Proceedings of the Annual Conference on Brazilian Symposium on Information Systems, Information Systems: A Computer Socio-Technical Perspective, SBSI 2015, Goiania, Brazil, May 26–29, 2015, pp. 219–226 (2015)

    Google Scholar 

  7. Chiu, C.-C., Chuang, C.-M., Hsu, C.-Y.: A novel personal identity verification approach using a discrete wavelet transform of the ECG signal. In: Proceedings of 2008 International Conference on Multimedia and Ubiquitous Engineering (MUE 2008), pp. 201–206 (2008)

    Google Scholar 

  8. Li, Y., et al.: A survey of multimodal fusion for identity verification. Journal of Physics Conference Series, pp. 1–5 (2020)

    Google Scholar 

  9. Wang, Y., Wang, Y., Tan, T.: Combining fingerprint and voiceprint biometrics for identity verification: an experimental comparison. In: Zhang, D., Jain, A.K. (eds.) ICBA 2004. LNCS, vol. 3072, pp. 663–670. Springer, Heidelberg (2004). https://doi.org/10.1007/978-3-540-25948-0_90

    Chapter  Google Scholar 

  10. Cuzzocrea, A., Chakravarthy, S.: Event-based lossy compression for effective and efficient OLAP over data streams. Data Knowl. Eng. 69(7), 678–708 (2010)

    Article  Google Scholar 

  11. Bonifati, A., Cuzzocrea, A.: efficient fragmentation of large XML documents. In: Wagner, R., Revell, N., Pernul, G. (eds.) DEXA 2007. LNCS, vol. 4653, pp. 539–550. Springer, Heidelberg (2007). https://doi.org/10.1007/978-3-540-74469-6_53

    Chapter  Google Scholar 

  12. Cuzzocrea, A., Furfaro, F., Saccà, D.: Enabling OLAP in mobile environments via intelligent data cube compression techniques. J. Intell. Inf. Syst. 33(2), 95–143 (2009)

    Article  Google Scholar 

  13. Cuzzocrea, A., Darmont, J., Mahboubi, H.: Fragmenting Very Large XML data warehouses via K-means clustering algorithm. Int. J. Bus. Intell. Data Min. 4(3/4), 301–328 (2009)

    Google Scholar 

  14. Ceci, M., Cuzzocrea, A., Malerba, D.: Effectively and efficiently supporting roll-up and drill-down OLAP operations over continuous dimensions via hierarchical clustering. J. Intell. Inf. Syst. 44(3), 309–333 (2015)

    Article  Google Scholar 

  15. Pramanik, M.I., Lau, R.Y., Demirkan, H., Azad, M.A.K.: Smart health: big data enabled health paradigm within smart cities. Expert Syst. Appl. 87, 370–383 (2017)

    Article  Google Scholar 

  16. Lafuente, G.: The big data security challenge. Netw. Secur. 2015(1), 12–14 (2015)

    Article  Google Scholar 

  17. Kloch, C., Petersen, E.B., Madsen, O.B.: Cloud based infrastructure, the new business possibilities and barriers. Wireless Pers. Commun. 58(1), 17–30 (2011)

    Article  Google Scholar 

  18. Li, S., Da Xu, L., Zhao, S.: The internet of things: a survey. Inf. Syst. Front. 17(2), 243–259 (2015)

    Article  Google Scholar 

  19. Tolosana, R., Vera-Rodriguez, R., Fierrez, J., Ortega-Garcia, J.: Deepsign: deep on-line signature verification. IEEE Trans. Biom. Behav. Identity Sci. 3(2), 229–239 (2021)

    Google Scholar 

  20. Marx, V.: The big challenges of big data. Nature 498(7453), 255–260 (2013)

    Article  Google Scholar 

  21. Verlinde, P., Chollet, G., Acheroy, M.: Multi-modal identity verification using expert fusion. Inf. Fusion 1(1), 17–33 (2000)

    Article  Google Scholar 

  22. Oh, K., Oh, B., Toh, K., Yau, W., Eng, H.: Combining sclera and periocular features for multi-modal identity verification. Neurocomputing 128, 185–198 (2014)

    Article  Google Scholar 

  23. Zhang, S., et al.: CASIA-SURF: a large-scale multi-modal benchmark for face anti-spoofing. IEEE Trans. Biom. Behav. Identity Sci. 2(2), 182–193 (2020)

    Article  Google Scholar 

  24. Bai, Q., Xia, W., Yin, F., Yang, Y.: Identity-Guided Face Generation with Multi-Modal Contour Conditions, CoRR, vol. abs/2110.04854 (2021)

    Google Scholar 

  25. Spinoulas, L., Mirzaalian, H., Hussein, M.E., Abd Almageed, W.: Multi-modal fingerprint presentation attack detection: evaluation on a new dataset. IEEE Trans. Biom. Behav. Identity Sci. 3(3), 347–364 (2021)

    Google Scholar 

  26. Shafer, G.: A mathematical theory of evidence turns 40. Int. J. Approx. Reason. 79, 7–25 (2016)

    Article  MathSciNet  Google Scholar 

  27. Bimbot, F., et al.: A tutorial on text-independent speaker verification. EURASIP J. Adv. Signal Process. 2004(4), 1–22 (2004). https://doi.org/10.1155/S1110865704310024

    Article  Google Scholar 

  28. Molau, S., Pitz, M., Schluter, R., Ney, H.: Computing mel-frequency cepstral coefficients on the power spectrum. In: 2001 IEEE International Conference on Acoustics, Speech, And Signal Processing. Proceedings (cat. No. 01CH37221), vol. 1, pp. 73–76 (2001)

    Google Scholar 

  29. Yager, N., Amin, A.: Fingerprint verification based on minutiae features: a review. Pattern Anal. Appl. 7(1), 94–113 (2004)

    Article  MathSciNet  Google Scholar 

  30. Bellomo, F., Beritelli, F., Sciacca, E.: Robustness of forensic speaker verification systems based on alizelia_ral toolkit. In: Proceedings of IEEE Workshop on Biometric Measurements and Systems for Security and Medical Applications (BIOMS), pp. 1–6 (2014)

    Google Scholar 

  31. Bonastre, J.F., Wils, F., Meignier, S.: Alize, a free toolkit for speaker recognition. In: IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP ’05, Philadelphia, Pennsylvania, USA, March 18–23, 2005, pp. 737–740 (2005)

    Google Scholar 

  32. Campanella, S., Belin, P.: Integrating face and voice in person perception. Trends Cogn. Sci. 11(12), 535–543 (2007)

    Article  Google Scholar 

  33. Kumar, A., Wong, D.C.M., Shen, H.C., Jain, A.K.: Personal verification using palmprint and hand geometry biometric. In: Kittler, J., Nixon, M.S. (eds.) AVBPA 2003. LNCS, vol. 2688, pp. 668–678. Springer, Heidelberg (2003). https://doi.org/10.1007/3-540-44887-X_78

    Chapter  Google Scholar 

  34. Monwar, M.M., Gavrilova, M.: Fes: a system for combining face, ear and signature biometrics using rank level fusion. In: Proceedings of Fifth International Conference on Information Technology: New Generations (ITNG 2008), pp. 922–927 (2008)

    Google Scholar 

  35. Cannataro, M., Cuzzocrea, A., Mastroianni, C., Ortale, R., Pugliese, A.: Modeling adaptive hypermedia with an object-oriented approach and XML. In: Proceedings of the Second International Workshop on Web Dynamics, WebDyn@WWW 2002, pp. 35–44 (2002)

    Google Scholar 

  36. Bellatreche, L., Cuzzocrea, A., Benkrid, S.: F&A: a methodology for effectively and efficiently designing parallel relational data warehouses on heterogenous database clusters. In: Proceedings of the 12th International Conference on Data Warehousing and Knowledge Discovery (DAWAK 2010), pp. 89–104 (2010)

    Google Scholar 

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Acknowledgements

This research has been partially supported by the French PIA project “Lorraine Université d’Excellence”, reference ANR-15-IDEX-04-LUE.

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Authors and Affiliations

  1. iDEA Lab, University of Calabria, Rende, Italy

    Alfredo Cuzzocrea, Majid Abbasi Sisara & Carmine Gallo

  2. LORIA, University of Lorraine, Nancy, France

    Alfredo Cuzzocrea

  3. DIA Department, University of Trieste, Trieste, Italy

    Majid Abbasi Sisara

Authors
  1. Alfredo Cuzzocrea
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  2. Majid Abbasi Sisara
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  3. Carmine Gallo
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Corresponding author

Correspondence to Alfredo Cuzzocrea .

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Editors and Affiliations

  1. Department of Information and Communication Engineering, Fukuoka Institute of Technology, Fukuoka, Japan

    Leonard Barolli

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Cuzzocrea, A., Sisara, M.A., Gallo, C. (2022). Experimental Analysis and Verification of a Multi-modal-Biometrics Identity Verification Framework Based on the Dempster-Shafer Theory. In: Barolli, L. (eds) Complex, Intelligent and Software Intensive Systems. CISIS 2022. Lecture Notes in Networks and Systems, vol 497. Springer, Cham. https://doi.org/10.1007/978-3-031-08812-4_12

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