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A Model for Biometric Selection in Public Services Sector

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Artificial Intelligence Research (SACAIR 2022)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1734))

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Abstract

The need to authenticate people using their biometric attributes and tighten information security in organisations significantly increased over the years and public services are no exception. Selecting suitable, robust, relevant and beneficial multimodal biometric attributes in public services environment for person authentication and access control is essential. The major challenge is deploying the wrong multimodal biometric technology in the organisation, which results in failed system deployment. Artificial intelligence (AI) has the potential to significantly drive the adoption and deployment of multimodal biometric authentication in public services. The study recommends a multimodal biometrics selection model for authentication to prevent fraudulent and invalid documents for identification. This study focuses on the human factor elements of public awareness, acceptance, perception and usability relevant to multimodal biometric deployment success. The formalised model proposed in the study could be of value to public services that need to deploy multimodal biometric authentication technologies, thereby minimising future failed deployments.

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References

  1. Ahmad, M., et al.: Security, usability, and biometric authentication scheme for electronic voting using multiple keys. Int. J. Distrib. Sens. Netw. 16(7), 1550147720944025 (2020)

    Article  MathSciNet  Google Scholar 

  2. Ajibade, P.: Technology acceptance model limitations and criticisms: exploring the practical applications and use in technology-related studies, mixed-method, and qualitative researches. Libr. Philos. Pract. 9, 197–255 (2018)

    Google Scholar 

  3. Ajzen, I., Fishbein, M., Lohmann, S., Albarracín, D.: The influence of attitudes on behaviour. In: The Handbook of Attitudes, pp. 197–255 (2018)

    Google Scholar 

  4. Ani, U.D., Watson, J.M., Nurse, J.R., Cook, A., Maples, C.: A review of critical infrastructure protection approaches: improving security through responsiveness to the dynamic modelling landscape (2019)

    Google Scholar 

  5. Beigi, H.: Access control through multifactor authentication with multimodal biometrics. United States patent US 10,042,993 [BCPRS13] Bolle RM, Connell JH, Pankanti NK (2018)

    Google Scholar 

  6. Boult, T.E., Woodworth, R.: Privacy and security enhancements in biometrics. A multimodal biometric system for secure identification. Asian J. Technol. Manag. Res. 5(02), 423–445 (2015)

    Google Scholar 

  7. Chanukya, P.S.V.V.N., Thivakaran, T.K.: Multimodal biometric cryptosystem for human authentication using fingerprint and ear. Multimed. Tools Appl. 79(1), 659–673 (2020)

    Article  Google Scholar 

  8. Datta, P., Bhardwaj, S., Panda, S.N., Tanwar, S., Badotra, S.: Survey of security and privacy issues on biometric system. In: Gupta, B.B., Perez, G.M., Agrawal, D.P., Gupta, D. (eds.) Handbook of Computer Networks and Cyber Security, pp. 763–776. Springer, Cham (2020). https://doi.org/10.1007/978-3-030-22277-2_30

    Chapter  Google Scholar 

  9. Dwivedi, Y.K., Rana, N.P., Jeyaraj, A., Clement, M., Williams, M.D.: Re-examining the unified theory of acceptance and use of technology (UTAUT): towards a revised theoretical model. Inf. Syst. Front. 21(3), 719–734 (2019)

    Article  Google Scholar 

  10. El-Abed, M.: Usability assessment of keystroke dynamics systems. Int. J. Comput. Appl. Technol. 55(3), 222–231 (2017)

    Article  Google Scholar 

  11. Farrell, S.: Biometrics in air transport: no flight of fancy. Biometr. Technol. Today 2019(1), 5–7 (2019)

    Article  Google Scholar 

  12. Furnell, S., Evangelatos, K.: Public awareness and perceptions of biometrics. Comput. Fraud Secur. 2007(1), 8–13 (2007)

    Article  Google Scholar 

  13. Genovese, A., Muñoz, E., Piuri, V., Scotti, F.: Advanced biometric technologies: emerging scenarios and research trends. In: Samarati, P., Ray, I., Ray, I. (eds.) From Database to Cyber Security. LNCS, vol. 11170, pp. 324–352. Springer, Cham (2018). https://doi.org/10.1007/978-3-030-04834-1_17

    Chapter  Google Scholar 

  14. Goldstein, J., Angeletti, R., Holzbach, M., Konrad, D., Snijder, M.: Large-scale biometrics deployment in Europe: identifying challenges and threats. JRC Scientific and Technical Reports (2008)

    Google Scholar 

  15. Kannammal, A., Prasanalakshmi, B.: Analysing security measures with unimodal and multimodal biometrics. In: International Conference on Sensors, Security, Software and Intelligent Systems, Beijing (2009)

    Google Scholar 

  16. Mikalef, P., et al.: Enabling AI capabilities in government agencies: a study of determinants for European municipalities. Gov. Inf. Q. 39, 101596 (2021)

    Article  Google Scholar 

  17. Myers, D., Willingham, M., Stewart, K.: Law enforcement guide to false identification. Pacific Institute for Research and Evaluation, Beltsville, MD (2001)

    Google Scholar 

  18. Nag, A.K., Dasgupta, D., Deb, K.: An adaptive approach for active multi-factor authentication. In: 9th Annual Symposium on Information Assurance (ASIA14), vol. 39 (2014)

    Google Scholar 

  19. Oh, J., Lee, U., Lee, K.: Usability evaluation model for biometric system considering privacy concern based on MCDM model. In: Security and Communication Networks (2019)

    Google Scholar 

  20. Omolara, O.O., Reginald, A.C., Oyedepo, O.M., Wasiat, E.A., Taiwo, O.A.: Modelling and simulation of Nigerian airspace management agency billing system using Python simulation packages. Am. J. Math. Comput. Model. 5(4), 109–115 (2020)

    Article  Google Scholar 

  21. Plaatjies, P.: National training framework for road traffic management. In: SATC 2010 (2010)

    Google Scholar 

  22. Pooe, A., Labuschagne, L.: Factors impacting on the adoption of biometric technology by South African banks: an empirical investigation. South. Afr. Bus. Rev. 15(1), 20 (2011)

    Google Scholar 

  23. Ramakumar, N., Reddy, P.S.N., Naik, R.N., Jilani, S.A.K.: Authentication based systematic driving license issuing system. In: 2017 International Conference on Intelligent Computing and Control Systems (ICICCS), pp. 1327–1331. IEEE (2017)

    Google Scholar 

  24. Rommetveit, K.: Introducing biometrics in the European Union: practice and imagination. In: Delgado, A. (ed.) Technoscience and Citizenship: Ethics and Governance in the Digital Society. TILELT, vol. 17, pp. 113–126. Springer, Cham (2016). https://doi.org/10.1007/978-3-319-32414-2_8

    Chapter  Google Scholar 

  25. Sagberg, F.: Characteristics of fatal road crashes involving unlicensed drivers or riders: implications for countermeasures. Accid. Anal. Prev. 117, 270–275 (2018)

    Article  Google Scholar 

  26. Sailaja, D., Navya Sri, M., Samuel, P.: An biometric-based embedded system for e-verification of vehicle users for RTO. In: Bhateja, V., Satapathy, S., Zhang, Y.D., Aradhya, V. (eds.) ICICC 2019. AISC, vol. 1034, pp. 711–718. Springer, Singapore (2019). https://doi.org/10.1007/978-981-15-1084-7_69

  27. Sam, D., Velanganni, C., Evangelin, T.E.: A vehicle control system using a time synchronized Hybrid VANET to reduce road accidents caused by human error. Veh. Commun. 6, 17–28 (2016)

    Google Scholar 

  28. Sathye, M., Dugdale, A.: Fraud in e-government transactions risks and remedies. In: Business evaluation of Government Conference and e-Government, pp. 41–52. Australian Government/IPAA (2004)

    Google Scholar 

  29. Sharma, V.: Aadhaar-a unique identification number: opportunities and challenges ahead. Res. Cell: Int. J. Eng. Sci. 4(2), 169–176 (2011)

    Google Scholar 

  30. Smith, M., Mann, M., Urbas, G.: Biometrics, Crime and Security. Routledge, Abingdon (2018)

    Google Scholar 

  31. Sujithra, M., Padmavathi, G.: A survey of biometric iris recognition: security, techniques and metrics. Asian J. Inf. Technol. 14(6), 192–199 (2015)

    Google Scholar 

  32. Thakur, K., Vyas, P.: Social impact of biometric technology: myth and implications of biometrics: issues and challenges. In: Sinha, G.R. (ed.) Advances in Biometrics, pp. 129–155. Springer, Cham (2019). https://doi.org/10.1007/978-3-030-30436-2_7

    Chapter  Google Scholar 

  33. Venkatesh, V., Morris, M.G., Davis, G.B., Davis, F.D.: User acceptance of information technology: toward a unified view. MIS Q. 27, 425–478 (2003)

    Article  Google Scholar 

  34. Whitman, R.: Information security: a study on biometric security solutions for telecare medical information systems. Doctoral dissertation. University of New Hampshire (2016)

    Google Scholar 

  35. Wolf, F., Kuber, R., Aviv, A.J.: An empirical study examining the perceptions and behaviours of security-conscious users of mobile authentication. Behav. Inf. Technol. 37(4), 320–334 (2018)

    Article  Google Scholar 

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Author information

Authors and Affiliations

  1. University of Johannesburg, Auckland Park, PO Box 524, Johannesburg, 2006, South Africa

    Mapula Elisa Maeko & Dustin van der Haar

Authors
  1. Mapula Elisa Maeko
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  2. Dustin van der Haar
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Correspondence to Dustin van der Haar .

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Editors and Affiliations

  1. University of KwaZulu-Natal, Durban, South Africa

    Anban Pillay

  2. University of KwaZulu-Natal, Durban, South Africa

    Edgar Jembere

  3. University of Pretoria, Pretoria, South Africa

    Aurona Gerber

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Maeko, M.E., van der Haar, D. (2022). A Model for Biometric Selection in Public Services Sector. In: Pillay, A., Jembere, E., Gerber, A. (eds) Artificial Intelligence Research. SACAIR 2022. Communications in Computer and Information Science, vol 1734. Springer, Cham. https://doi.org/10.1007/978-3-031-22321-1_22

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  • DOI: https://doi.org/10.1007/978-3-031-22321-1_22

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-22320-4

  • Online ISBN: 978-3-031-22321-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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