Evolution of User Authentication Methods in Mobile Phones: A Security Perspective

  • Authors

    • Deborah Ooi Yee Hui
    • Kok Kian Yuen
    • Bibi Asha Farina Binti Shikh Mohd Zahor
    • Kelvin Lim Ching Wei
    • Zarul Fitri Zaaba
    • Renas Rajab Asaad
    https://doi.org/10.14419/ijet.v7i4.19.23177

    Received date: December 5, 2018

    Accepted date: December 5, 2018

    Published date: November 27, 2018

  • User authentication, fingerprint recognition, iris recognition, voiceprint recognition, face recognition, security
  • Abstract

    There are many ways of performing user authentication in mobile phones. Back then, a specific button is assigned as a security lock button such as the asterisk yet major concerns on security issues over personal data stored in mobile phones have been raised. Password-based authentication took over the trend with pattern and PIN unlock being commonly used by users of mobile phones. However, these methods are still prone to fraud as unethical users tend to break the passcode using shoulder surfing or hacking. To further strengthen the security in mobile phones, biometric authentication approaches are proposed. In this paper, four biometric-based authentication methods are being compared through a several aspects. As a result, the most significant biometric-based authentication approach is presented.

  • References

    1. Kemp, S., ‘Digital in 2017: Global Overview.’ We Are Social, 2017,https://wearesocial.com/special-reports/digital-in-2017-global-overview. Accessed 9 October 2017.
    2. Bursztein, E., ‘Survey: Most People Don’t Lock Their Android Phones – But Should.’ Elie, 2014,
    3. https://www.elie.net/blog/survey-most-people-dont-lock-their-android-p hones-but-should. Accessed 10 October 2017.
    4. Baldwin, R., ‘Don’t Be Silly. Lock Down and Encrypt Your Smartphone.’ Wired, 2013, http://www.wired.com/2013/10/keep-your-smartphone-locked. Accessed 10 October 2017.
    5. Harbach, M., De Luca, A. & Egelman, S., “The Anatomy of Smartphone Unlocking: A Field Study of Android Lock Screens,” in CHI ’16 Proceedings of the 34th Annual ACM Conference on Human Factors in Computing System, San Jose, CA, 2016, pp. 4806-4817.
    6. Schlöglhofer, R. & Sametinger, J., “Secure and Usable Authentica-tion on Mobile Devices,” in The 10th International Conference on Advanced Computing & Multimedia, Bali, 2012, pp. 257-262.
    7. “Biometrics.” Def. 2. Merriam-Webster Online. Meriam-Webster, 2017. Web. Accessed 10 October 2017.
    8. Mohammed, S. K. & Fajri, K., “A Review of Fingerprint Pre-processing Using A Mobile Phone,” in Proceedings of the 2012 In-ternational Conference on Wavelet Analysis and Pattern Recogni-tion, Xian, China, 2012, pp. 152-157.
    9. Ijiri, Y., Sakuragi, M. & Shihong, L., “Security Management for Mobile Devices by Face Recognition,” in The 7th International Conference on Mobile Data Management, Nara, Japan, 2006.
    10. Hadid, A., Heikkild, J. Y., Silven, O. & Pietikdinen, M., “Face and Eye Detection For Person Authentication In Mobile Phones,” in First ACM/IEEE International Conference on Distributed Smart Cameras, Vienna, Austria, 2007.
    11. Jain, A., “Biometric Recognition: How Do I Know Who You Are?,” in Proceedings of the IEEE 12th Signal Processing and Communi-cations Applications Conference 2004, Kusadasi, Turkey, 2004.
    12. Kim, Dongik, Jung, Yujin, Toh, Kar-Ann, Son, Byungjun & Kim, Jaihie., “An Empirical Study on Iris Recognition in a Mobile Phone,” in Expert Systems with Applications, Tarrytown, New York, 2016, pp. 328-339.
    13. S., C. S., & Shinde, G. N., “Iris Biometrics Recognition Application in Security Management,” in 2008 Congress on Image and Signal Processing, Sanya, China 2008.
    14. Delac, K. & Grgic, M., “A Survey on Biometric Methods,” in 46th International Symposium Electronics in Marine, Zadar, Croatia, 2004, pp. 184-193.
    15. Bhattacharyya, D., Ranjan, R., Alisherov, F. & Minkyu, C., “Bio-metric Authentication: A Review,” in International Journal of u- and e- Service, Science and Technology, Vol. 2(3), Australia, 2009, pp. 13-28.
    16. Philips, P. J., Martin, A., Wilson, C. L. & Przybocki, M., “An Intro-duction to Evaluating Biometric Systems,” in Computer, Vol. 33(2), Los Alamitos, California, 2000, pp. 56-63.
    17. Anil, K. J., Jianjiang, F. & Karthik, N., “Fingerprint Matching,” in Computer, Vol. 43(2), Los Alamitos, California, 2010, pp. 36-44.
    18. Anil K. J., Ross, A. & Prabhakar, S., “An Introduction to Biometric Recognition,” in IEEE Transactions on Circuits and Systems for Video Technology, Vol. 14 (1), 2004, pp. 4-20.
    19. Viola, P. & Jones, M., “Rapid Object Detection Using A Boosted Cascade of Simple Features,” in Proceedings of the 2001 IEEE Computer Science Society Conference on Computer Vision and Pattern Recognition, Kauai, Hawaii, 2001.
    20. Wildes, R. P., “Iris Recognitions: An Emerging Biometric Technol-ogy,” in Proceedings of the IEEE, Vol. 85(9), Princeton, New Jer-sey, 1997, pp. 1348-1363.
    21. Jeong, D. S., Park, H. A., Park, K. R. & Kim, J., “Iris Recognition in Mobile Phone Based on Adaptive Gabor Filter,” in Zhang, D. & Anil, K. J., (eds) Advances in Biometrics, ICB 2006. Lecture Notes in Computer Science, Vol. 3832, Berlin, Heidelberg: Springer, 2005.
    22. Zhang, J. & Chen, X. M., “A Research of Improved Algorithm for GMM Voiceprint Recognition Model,” in Control and Decision Conference (CCDC), Yinchuan, China, 2016, pp. 5560-5564.
    23. Shoup, A., Talkar, T., Chen, J. & Anil, K. J., An Overview and Analysis of Voice Authentication Methods, 2016. Unpublished manuscript.
    24. Anil, K. J., Sharath, P., Salil, P., Hong, L. & Arun, R., “Biometrics: A Grand Challenge,” in Proceedings of the 17th International Con-ference on Pattern Recognition, Cambridge, UK, 2004.
    25. Robert, G. Z. & Olsen, J., Voice Recognition Software Versus A Traditional Transcription Service For Physician Charting in the ED. Chicago, IL: University of Chicago Hospitals Section of Emergency Medicine, 2001.
    26. Matschitsch, S., Tschinder, M. & Uhl, A., “Comparison of Com-pression Algorithms’ Impact on Iris Recognition Accuracy,” in Lee, S. W. & Li, S. Z. (eds) Advances in Biometrics, ICB 2007. Lecture Notes in Computer Sciences, Vol. 4642. Berlin, Heidelberg: Spring-er, 2007.
    27. Dongik, K., Yujin, J., Kar-Ann, D., Byungjun, S., Jaihie, K., “An Empirical Study on Iris Recognition in a Mobile Phone,” in Expert Systems with Applications, Vol. 54, Tarrytown, New York, 2016, pp. 328-339.
    28. Cappelli, R., Maio, D., Maltoni, D., Wayman, J. & Anil, K. J., “Per-formance Evaluation of Fingerprint Verification Systems,” in IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 28(1), 2006, pp. 3-18.
    29. Clarke, N. L., Furnell, S. M. & Reynolds, P. L., “Biometric Authen-tication for Mobile Devices,” in 3rd Australian Information Welfare and Security Conference, Sydney, Australia, 2002, pp. 61-69.
    30. Gao, M., Hu, X., Cao, B. & Li, D., “Fingerprint Sensors in Mobile Devices,” in IEEE 9th Conference on Industrial Electronics and Applications, Hangzhou, China, 2014, pp. 1437-1440.
    31. Choi, K., Toh, K. & Byun, H., “Realtime Training on Mobile De-vices for Face Recognition Applications,” in Pattern Recognition, Vol. 42(2), 2011, pp. 386-400.
    32. Andrew, S. P., ‘Fingerprint Concerns: Performance, Usability and Acceptance of Fingerprint Biometric Systems.’ 2008, https://www.andrewpatrick.ca/essays/fingerprint-concerns-performance-usability-and-acceptance-of-fingerprint-biometric-systems. Accessed 19 November 2017.
    33. Nixon, K., Aimale, V., Rowe, R., Anil, K. J., Flynn, P. & Ross, A., Spoof Detection Schemes in Handbook of Biometrics, pp. 403-423. New York, NY: Springer-Verlag, 2008.
    34. Erdogmus, N. & Marcel, S., “Spoofing Face Recognition with 3D Masks,” in IEEE Transactions on Information Forensics and Securi-ty, Vol. 9(7), 2014, pp. 1084-1097.
    35. Rabiner, L. R., “A Tutorial on Hidden Markov Models and Select-ed Applications in Speech Recognition,” in Proceedings of the IEEE 77.2, 2011, pp. 257-286.
    36. Shafique, U., Sher, A., Ullah, R., Hikmat, K., Zeb, A., Ullah, R., Waqar, S., Shafi, U., Bashir, F. & Shah, M. A., “Modern Authenti-cation Technique in Smart Phones: Security and Usability Perspec-tive,” in International Journal of Advanced Computer Sciences and Applications, Vol. 8(1), 2017, pp. 331-335.
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    Ooi Yee Hui, D., Kian Yuen, K., Asha Farina Binti Shikh Mohd Zahor, B., Lim Ching Wei, K., Fitri Zaaba, Z., & Rajab Asaad, R. (2018). Evolution of User Authentication Methods in Mobile Phones: A Security Perspective. International Journal of Engineering and Technology, 7(4.19), 425-429. https://doi.org/10.14419/ijet.v7i4.19.23177