DOI QR코드

DOI QR Code

Review of Biometrics-Based Authentication Techniques in Mobile Ecosystem

  • Al-Jarba, Fatimah (Information Systems Department, Imam Mohammad Ibn Saud Islamic University) ;
  • Al-Khathami, Mohammed (Information Systems Department, Imam Mohammad Ibn Saud Islamic University)
  • Received : 2021.11.05
  • Published : 2021.11.30

Abstract

Mobile devices have recently developed to be an integral part of humans' daily lives because they meet business and personal needs. It is challenging to design a feasible and effective user authentication method for mobile devices because security issues and data privacy threats have significantly increased. Biometric approaches are more effective than traditional authentication methods. Therefore, this paper aims to analyze the existing biometric user authentication methods on mobile platforms, particularly those that use face recognition, to demonstrate the methods' feasibility and challenges. Next, this paper evaluates the methods according to seven characteristics: universality, uniqueness, permanence, collectability, performance, acceptability, and circumvention. Last, this paper suggests that solely using the method of biometric authentication is not enough to identify whether users are authentic based on biometric traits.

Keywords

References

  1. "Number of smartphone users in the United States from 2018 to 2025," Statista. https://www.statista.com/statistics/201182/forecast-of-smartphone-users-in-the-us/ (accessed Aug. 23, 2021).
  2. A. Shankar, C. Jebarajakirthy, and M. Ashaduzzaman, "How do electronic word of mouth practices contribute to mobile banking adoption?," J. Retail. Consum. Serv., vol. 52, p. 101920, 2020. https://doi.org/10.1016/j.jretconser.2019.101920
  3. C. B. Chakiso, "Factors affecting Attitudes towards Adoption of Mobile Banking: Users and Non-Users Perspectives," EMAJ Emerg. Mark. J., vol. 9, no. 1, pp. 54-62, 2019. https://doi.org/10.5195/emaj.2019.167
  4. C. Z. Maulana, Y. Suryana, D. Kartini, and E. Febrian, "Influencing Factors on the Actual Usage of Mobile Phone Banking in the Shari'ah Banks: A Survey in Palembang City, Indonesia," Glob. Rev. Islam. Econ. Bus., vol. 7, no. 1, pp. 001-019, 2019. https://doi.org/10.14421/grieb.2019.071-01
  5. A. W. Siyal, D. Donghong, W. A. Umrani, S. Siyal, and S. Bhand, "Predicting mobile banking acceptance and loyalty in Chinese bank customers," SAGE Open, vol. 9, no. 2, p. 2158244019844084, 2019.
  6. "Digital Market Outlook: mobile payment transaction value Spain 2022," Statista. https://www.statista.com/statistics/745931/mobile-payment-transaction-value-in-spain/ (accessed Feb. 23, 2020).
  7. B. N. Vuong, V. T. Hieu, and N. T. T. Trang, "An empirical analysis of mobile banking adoption in Vietnam," Gest. E Soc., vol. 14, no. 37, pp. 3365-3393, 2020.
  8. A. Massie, J. S. Lapian, and M. V. Tielung, FACTORS INFLUENCING CONSUMER ACCEPTANCE OF MOBILE BANKING AT SAM RATULANGI UNIVERSITY STUDENTS," J. EMBA J. Ris. Ekon. Manaj. Bisnis Dan Akunt., vol. 7, no. 4, 2019.
  9. S. Raju, "Customer Perception Towards Mobile Banking Services In Warangal Urban District of Telangana State-An Empirical Study," Our Herit., vol. 68, no. 1, pp. 7822-7832, 2020.
  10. I. Olade, H. Liang, and C. Fleming, "A Review of Multimodal Facial Biometric Authentication Methods in Mobile Devices and Their Application in Head Mounted Displays," in 2018 IEEE SmartWorld, Ubiquitous Intelligence & Computing, Advanced & Trusted Computing, Scalable Computing & Communications, Cloud & Big Data Computing, Internet of People and Smart City Innovation (SmartWorld/SCALCOM/UIC/ATC/CBDCom/IOP/SCI), 2018, pp. 1997-2004.
  11. W. Meng, D. S. Wong, S. Furnell, and J. Zhou, "Surveying the development of biometric user authentication on mobile phones," IEEE Commun. Surv. Tutor., vol. 17, no. 3, pp. 1268-1293, 2014. https://doi.org/10.1109/COMST.2014.2386915
  12. R. Jiang, S. Al-Maadeed, A. Bouridane, D. Crookes, and A. Beghdadi, Biometric Security and Privacy. Springer, 2017.
  13. P. Temdee and R. Prasad, Context-aware communication and computing: Applications for smart environment. Springer, 2018.
  14. V. Matyas and Z. Riha, "Toward reliable user authentication through biometrics," IEEE Secur. Priv., vol. 1, no. 3, pp. 45-49, May 2003, doi: 10.1109/MSECP.2003.1203221.
  15. J. Khan, H. Abbas, and J. Al-Muhtadi, "Survey on mobile user's data privacy threats and defense mechanisms," Procedia Comput. Sci., vol. 56, pp. 376-383, 2015. https://doi.org/10.1016/j.procs.2015.07.223
  16. L. Xie, H. Xian, X. Tang, W. Guo, F. Hang, and N. Fang, "G-Key: An Authentication Technique for Mobile Devices Based on Gravity Sensors," in 2019 IEEE International Conference on Power Data Science (ICPDS), 2019, pp. 126-129.
  17. L. Wu, J. Wang, K.-K. R. Choo, and D. He, "Secure key agreement and key protection for mobile device user authentication," IEEE Trans. Inf. Forensics Secur., vol. 14, no. 2, pp. 319-330, 2018. https://doi.org/10.1109/tifs.2018.2850299
  18. T. Zhu et al., "RiskCog: Unobtrusive real-time user authentication on mobile devices in the wild," IEEE Trans. Mob. Comput., 2019.
  19. T. Dahlberg, N. Mallat, J. Ondrus, and A. Zmijewska, "Electronic Commerce Research and Applications," Retrieved Novemb., vol. 6, p. 2011, 2007.
  20. K.-H. Yeh, "A secure transaction scheme with certificateless cryptographic primitives for IoT-based mobile payments," IEEE Syst. J., vol. 12, no. 2, pp. 2027-2038, 2018. https://doi.org/10.1109/jsyst.2017.2668389
  21. S. Parusheva, "A comparative study on the application of biometric technologies for authentication in online banking," Egypt. Comput. Sci. J., vol. 39, no. 4, pp. 116-127, 2015.
  22. P. Wang, W.-H. Lin, K.-M. Chao, and C.-C. Lo, "A face-recognition approach using deep reinforcement learning approach for user authentication," in 2017 IEEE 14th International Conference on e-Business Engineering (ICEBE), 2017, pp. 183-188.
  23. P. Samangouei, V. M. Patel, and R. Chellappa, "Attribute-based continuous user authentication on mobile devices," in 2015 IEEE 7th international conference on biometrics theory, applications and systems (BTAS), 2015, pp. 1-8.
  24. S. Acharya, A. Polawar, and P. Pawar, "Two factor authentication using smartphone generated one time password," IOSR J. Comput. Eng. IOSR-JCE, vol. 11, no. 2, pp. 85-90, 2013. https://doi.org/10.9790/0661-1128590
  25. A. Ometov, S. Bezzateev, N. Makitalo, S. Andreev, T. Mikkonen, and Y. Koucheryavy, "Multi-factor authentication: A survey," Cryptography, vol. 2, no. 1, p. 1, 2018. https://doi.org/10.3390/cryptography2010001
  26. D. Crouse, H. Han, D. Chandra, B. Barbello, and A. K. Jain, "Continuous authentication of mobile user: Fusion of face image and inertial measurement unit data," in 2015 International Conference on Biometrics (ICB), 2015, pp. 135-142.
  27. U. Mahbub, V. M. Patel, D. Chandra, B. Barbello, and R. Chellappa, "Partial face detection for continuous authentication," in 2016 IEEE International Conference on Image Processing (ICIP), 2016, pp. 2991-2995.
  28. M. E. Fathy, V. M. Patel, and R. Chellappa, "Face-based active authentication on mobile devices," in 2015 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2015, pp. 1687-1691.
  29. M. Du, "Mobile payment recognition technology based on face detection algorithm," Concurr. Comput. Pract. Exp., vol. 30, no. 22, p. e4655, 2018, doi: 10.1002/cpe.4655.
  30. D. Pal, P. Khethavath, T. Chen, and Y. Zhang, "Mobile payments in global markets using biometrics and cloud," Int. J. Commun. Syst., vol. 30, no. 14, p. e3293, 2017. https://doi.org/10.1002/dac.3293
  31. S. Mathur, A. Vjay, J. Shah, S. Das, and A. Malla, Methodology for partial fingerprint enrollment and authentication on mobile devices," in 2016 International Conference on Biometrics (ICB), 2016, pp. 1-8.
  32. S. Soviany, S. Puscoci, V. Sandulescu, and C. Soviany, "A biometric security model for mobile applications," Int. J. Commun., vol. 3, 2018.
  33. M. F. Islam and M. N. Islam, "A biometrics-based secure architecture for mobile computing," in 2012 IEEE Long Island Systems, Applications and Technology Conference (LISAT), 2012, pp. 1-5.
  34. K.-S. Wong and M. H. Kim, "An enhanced user authentication solution for mobile payment systems using wearables," Secur. Commun. Netw., vol. 9, no. 17, pp. 4639-4649, 2016. https://doi.org/10.1002/sec.1654
  35. O. Kerem, V. Coskun, B. Ozdenizci, and M. N. Aydin, "A role-based service level NFC ecosystem model," Wirel. Pers. Commun., vol. 68, no. 3, pp. 811-841, 2013. https://doi.org/10.1007/s11277-011-0484-3
  36. P. Vishwakarma, A. K. Tripathy, and S. Vemuru, "A hybrid security framework for Near Field Communication driven mobile payment model," vol. 14, no. 12, p. 12, 2016.
  37. S. S. Ahamad, I. Al-Shourbaji, and S. Al-Janabi, "A secure NFC mobile payment protocol based on biometrics with formal verification," Int. J. Internet Technol. Secur. Trans., vol. 6, no. 2, pp. 103-132, 2016. https://doi.org/10.1504/IJITST.2016.078579
  38. V. H. and J. Pagliery, "Nearly 1 million new malware threats released every day," CNNMoney, Apr. 14, 2015. https://money.cnn.com/2015/04/14/technology/security/cyber-attack-hacks-security/index.html (accessed Apr. 21, 2020).
  39. J. Andress, The basics of information security: understanding the fundamentals of InfoSec in theory and practice. Syngress, 2014.
  40. M. Sujithra and G. Padmavathi, "Next generation biometric security system: an approach for mobile device security," in Proceedings of the Second International Conference on Computational Science, Engineering and Information Technology - CCSEIT '12, Coimbatore UNK, India, 2012, pp. 377-381, doi: 10.1145/2393216.2393280.
  41. "Biometrics in 2020 (A helpful illustrated overview)." https://www.thalesgroup.com/en/markets/digitalidentity-and-security/government/inspired/biometrics (accessed Jun. 23, 2020).
  42. "biometrics / Authentication technologies." http://biometrics.pbworks.com/w/page/14811351/Authentication%20technologies#FacialRecognition (accessed Jun. 23, 2020).