Assessment of Biometric Identification – Part 1
Copyright (c) 2023 Bak Gerda, Kovács Tibor, Őszi Arnold
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
Abstract
Nowadays, biometric identification is becoming more and more common, as it is present in smartphones and is also used by many businesses that recognise its benefits. This study aims to assess the perceptions and opinions of users on biometric identification. The significance of the research lies in the fact that two studies with similar aims were conducted in 2006 and 2014, also at Óbuda University, which we tried to continue and further develop in the present research. The first part presents the part of the survey dealing with respondents’ awareness and use of biometric identification systems. Based on the results, it can be said that the users’ knowledge of biometric identification needs to be expanded, as many people still simply use these technologies without the corresponding knowledge and awareness.
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References
Ammour, Basma – Bouden, Toufik – Boubchir, Larbi (2018): Face-Iris Multimodal Biometric System Based on Hybrid Level Fusion. In 2018 41st International Conference on Telecommunications and Signal Processing (TSP). IEEE. 1–5. Online: https://doi.org/10.1109/TSP.2018.8441279
Cornacchia, Michele – Papa, Filomena – Sapio, Bartolomeo (2020): User Acceptance of Voice Biometrics in Managing the Physical Access to a Secure Area of an International Airport. Technology Analysis & Strategic Management, 32. évf. 10. sz. 1236–1250. Online: https://doi.org/10.1080/09537325.2020.1758655
Dargan, Shaveta – Kumar, Munish (2020): A Comprehensive Survey on the Biometric Recognition Systems Based on Physiological and Behavioral Modalities. Expert Systems with Applications, 143. évf. 113114. Online: https://doi.org/10.1016/j.eswa.2019.113114
Datta, Priyanka – Bhardwaj, Shanu – Panda, S. N. – Tanwar, Sarvesh – Badotra, Sumit (2020): Survey of Security and Privacy Issues on Biometric System. In Handbook of Computer Networks and Cyber Security. Cham, Springer. 763–776. Online: https://doi.org/10.1007/978-3-030-22277-2_30
Devi, R. Subathra – Sujatha, Pothula (2017): A Study on Biometric and Multi-Modal Biometric System Modules, Applications, Techniques and Challenges. In 2017 Conference on Emerging Devices and Smart Systems (ICEDSS). IEEE. 267–271. Online: https://doi.org/10.1109/ICEDSS.2017.8073691
Fejes Attila (2018): Beszéd alapján történő személyazonosítás új kihívásai a kriminalisztikában. Magyar Rendészet, 18. évf. 2. sz. 117–126.
Flynn, Patrick J. – Jain, Anil K. – Ross, Arun A. (2008): Introduction to Biometrics. In Handbook of Biometrics. Boston, MA, Springer, 2008, 1–22.
Földesi Krisztina (2015): Paradigmaváltás a biztonságtechnikában — miért alkalmazzunk biometrikus rendszert? Magyar Rendészet, 15. évf. 3. sz. 37–48.
Gad, Ramadan – El-Sayed, Ayman – El-Fishawy, Nawal – Zorkany, M. (2015): Multi-Biometric Systems: A State of the Art Survey and Research Directions. (IJACSA) International Journal of Advanced Computer Science and Applications, 6. évf. 6. sz. 128–138. Online: https://doi.org/10.14569/IJACSA.2015.060618
Hazai Lászlóné (2019): Módszerek, technikák a biometrikus arcfelismerésben, -azonosításban. Belügyi Szemle, 67. évf. 1. sz. 118–126. Online: https://doi.org/10.38146/BSZ.2019.1.9
Hino, Hayiel (2015): Assessing Factors Affecting Consumers’ Intention to Adopt Biometric Authentication Technology in E-shopping. Journal of Internet Commerce, 14. évf. 1. sz. 1–20. Online: https://doi.org/10.1080/15332861.2015.1006517
IBM (2018): IBM Security: Future of Identity Study. IBM, 2021. december 10. Online: https://www.ibm.com/downloads/cas/PL9VJ9KV
Jain, Anil K. – Ross, Arun – Prabhakar, Salil (2004): An Introduction to Biometric Recognition. IEEE Transactions on Circuits and Systems for Video Technology, 14. évf. 1. sz. 4–20. Online: https://doi.org/10.1109/TCSVT.2003.818349
Kovács Tibor – Földesi Krisztina (2021): Összehasonlító kutatáselemzés a biometrikus személyazonosító-beléptető rendszerek, eljárások 2006. és 2014. évi társadalmi averzív reakcióinak vizsgálatára. SecureInfo, 2021. december 10. Online: https://www.securinfo.hu/wp-content/uploads/2015/06/20150602_osszehasonlito_elemzes_a_biometrikus_szemelyazonosito_rendszerek.pdf
Liu, Shanhong (2021): Biometric Technologies – Statistics & Facts. Statista, 2021. október 30. Online: https://www.statista.com/topics/4989/biometric-technologies/#dossierKeyfigures
Norfolk, Lauren – O’Regan, Michael (2020): Biometric Technologies at Music Festivals: An Extended Technology Acceptance Model. Journal of Convention & Event Tourism, 22. évf. 1. sz. 36–60. Online: https://doi.org/10.1080/15470148.2020.1811184
Rui, Zhang – Yan, Zheng (2019): A Survey on Biometric Authentication: Toward Secure and Privacy-Preserving Identification. IEEE Access, 7. évf. 5994–6009. Online: https://doi.org/10.1109/ACCESS.2018.2889996
Sarhan, Shahenda – Alhassan, Shaaban – Elmougy, Samir (2016): Multimodal Biometric Systems: A Comparative Study. Arabian Journal for Science and Engineering, 42. évf. 2. sz. 443–457. Online: https://doi.org/10.1007/s13369-016-2241-0
Shen, Chao – Chen, Yufei – Guan, Xiaohong (2018): Performance Evaluation of Implicit Smartphones Authentication via Sensor-Behavior Analysis. Information Sciences, 430–431. évf. 538–553. Online: https://doi.org/10.1016/j.ins.2017.11.058
Szűcs, Kata Rebeka – Őszi, Arnold – Kovács, Tibor (2020): Mobile Biometrics and their Risks. Hadmérnök, 15. évf. 4. sz. 15–28. Online: https://doi.org/10.32567/hm.2020.4.2
Tanviruzzaman, Mohammad – Ahamed, Sheikh Iqbal – Hasan, Chowdhury Sharif – O’Brien, Casey (2009): ePet: When Cellular Phone Learns to Recognize Its Owner. In SafeConfig ‘09: Proceedings of the 2nd ACM Workshop on Assurable and Usable Security Configuration. ACM. 13–18. Online: https://doi.org/10.1145/1655062.1655066