Skip to main content

An Adaptive and Viable Face Identification for Android Mobile Devices

  • Chapter
  • First Online:
Handbook of Multimedia Information Security: Techniques and Applications

Abstract

Smartphones apart from enjoying access to personal data, are increasingly being used for performing sensitive and critical financial transactions. Thus, making smartphones vulnerable to numerous contemporary threats as strong security solutions were not developed while considering resource-constrained devices like mobile phones in mind. A need for such a security solution persists that is capable of delivering strong security without compromising user convenience. Biometric tends to offer unparalleled user convenience. Although sparse usage of the face and fingerprint biometrics appear on mobile phone devices. However, their application is limited to mere device unlocking. The low accuracy offered by such solutions results in low user acceptance and limits their use in other security solutions. Therefore, it is evident that the recognition accuracy has to be inspected and improved to deal with the real-world situations. In this chapter, an adaptive face identification capable of minimizing the variations of real-world uncontrollable situations has been developed primarily on Android mobile devices while investigating the state of art algorithms in the field of face identification; Face Detection: Haar detector, Local Binary Patterns (LBP) detector; Face Identification: Principal Component Analysis (PCA), Linear Discriminant Analysis (LDA), Local Binary Patterns Histograms (LBPH).

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 219.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 279.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 279.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Abbas, N., Zhang, Y., Taherkordi, A. and Skeie, T., 2018. Mobile edge computing: A survey. IEEE Internet of Things Journal, 5(1), pp. 450-465.

    Article  Google Scholar 

  2. Adhikary, N., Shrivastava, R., Kumar, A., Verma, S.K., Bag, M. and Singh, V., 2012. Battering keyloggers and screen recording software by fabricating passwords. International Journal of Computer Network and Information Security, 4(5), p.13.

    Article  Google Scholar 

  3. Ambalakat, P., 2005, April. Security of biometric authentication systems. In 21st Computer Science Seminar (p. 1).

    Google Scholar 

  4. Andreeva, E., 2012, September. Secret sharing in continuous access control system, using heart sounds. In Problems of Redundancy in Information and Control Systems (RED), 2012 XIII International Symposium on (pp. 5-6). IEEE.

    Google Scholar 

  5. Aviv, A.J., Gibson, K.L., Mossop, E., Blaze, M. and Smith, J.M., 2010. Smudge Attacks on Smartphone Touch Screens. Woot, 10, pp. 1-7.

    Google Scholar 

  6. Bao, W., Li, H., Li, N. and Jiang, W., 2009, April. A liveness detection method for face recognition based on optical flow field. In Image Analysis and Signal Processing, 2009. IASP 2009. International Conference on (pp. 233-236). IEEE.

    Google Scholar 

  7. Buriro, A., Gupta, S. and Crispo, B., 2017. Evaluation of Motion-based Touch-typing Biometrics for online Banking.

    Google Scholar 

  8. Chingovska, I., Anjos, A. and Marcel, S., 2012. On the effectiveness of local binary patterns in face anti-spoofing. In Proceedings of the 11th International Conference of the Biometrics Special Interes Group (No. EPFL-CONF-192369).

    Google Scholar 

  9. Coldewey D. NIST declares the age of SMS-based 2-factor authentication over [Online]. TechCrunch. 2018. https://beta.techcrunch.com/2016/07/25/nist-declares-the-age-of-sms-based-2-factor-authentication-over/ [Accessed 30 April 2018].

  10. Conklin, A., Dietrich, G. and Walz, D., 2004, January. Password-based authentication: a system perspective. In System Sciences, 2004. Proceedings of the 37th Annual Hawaii International Conference on (pp. 10-pp). IEEE.

    Google Scholar 

  11. Darwaish, S.F., Moradian, E., Rahmani, T. and Knauer, M., 2014. Biometric identification on Android smartphones. Procedia Computer Science, 35, pp.832-841.

    Article  Google Scholar 

  12. De Marsico, M., Galdi, C., Nappi, M. and Riccio, D., 2014. Firme: Face and iris recognition for mobile engagement. Image and Vision Computing, 32(12), pp.1161-1172.

    Article  Google Scholar 

  13. Elftmann, P., 2006. Secure alternatives to password-based authentication mechanisms. Lab. for Dependable Distributed Systems, RWTH Aachen Univ.

    Google Scholar 

  14. Goel, C.K. and Arya, G., 2012. Hacking of passwords in windows environment. International Journal of Computer Science & Communication Networks, 2(3), pp.430-435.

    Google Scholar 

  15. Grahakseva, Online fraud happened hacking my icici bank credit card [Online]. 2013 http://www.grahakseva.com/complaints/130310/online-fraud-happened-hacking-my-icici-bank-credit-card [Accessed 30 April 2018].

  16. Hu, J., Peng, L. and Zheng, L., 2015, August. XFace: a face recognition system for Android mobile phones. In Cyber-Physical Systems, Networks, and Applications (CPSNA), 2015 IEEE 3rd International Conference on (pp. 13-18). IEEE.

    Google Scholar 

  17. Hussain, S., Khan, B.U.I., Anwar, F. and Olanrewaju, R.F., 2018. Secure annihilation of out-of-band authorization for online transactions. Indian Journal of Science and Technology, 11(5), pp.1-9.

    Article  Google Scholar 

  18. Islam, S.H. and Biswas, G.P., 2011. A more efficient and secure ID-based remote mutual authentication with key agreement scheme for mobile devices on elliptic curve cryptosystem. Journal of Systems and Software, 84(11), pp.1892-1898.

    Article  Google Scholar 

  19. Jain, A.K., Ross, A. and Pankanti, S., 2006. Biometrics: a tool for information security. IEEE transactions on information forensics and security, 1(2), pp.125-143.

    Article  Google Scholar 

  20. Jee, H.K., Jung, S.U. and Yoo, J.H., 2006. Liveness detection for embedded face recognition system. International Journal of Biological and Medical Sciences, 1(4), pp.235-238.

    Google Scholar 

  21. Khan, B.U.I., Baba, A.M., Olanrewaju, R.F., Lone, S.A. and Zulkurnain, N.F., 2015, August. SSM: Secure-Split-Merge data distribution in cloud infrastructure. In Open Systems (ICOS), 2015 IEEE Conference on (pp. 40-45). IEEE.

    Google Scholar 

  22. Khan, B.U.I., Olanrewaju, R.F., Baba, A.M., Langoo, A.A. and Assad, S., 2017. A compendious study of online payment systems: Past developments, present impact, and future considerations. International Journal of Advanced Computer Science and Applications, 8(5), pp.256-71.

    Google Scholar 

  23. Kizza, J.M., 2007. Ethical and social issues in the information age (Vol. 999). Springer.

    Google Scholar 

  24. Kumar, S., Singh, S.K., Singh, R.S., Singh, A.K. and Tiwari, S., 2017. Real-time recognition of cattle using animal biometrics. Journal of Real-Time Image Processing, 13(3), pp.505-526.

    Article  Google Scholar 

  25. Lovisotto, G., Malik, R., Sluganovic, I., Roeschlin, M., Trueman, P. and Martinovic, I., 2017. Mobile biometrics in financial services: A five factor framework. Technical Report CS-RR-17-03, Oxford University.

    Google Scholar 

  26. Määttä, J., Hadid, A. and Pietikäinen, M., 2011, October. Face spoofing detection from single images using micro-texture analysis. In Biometrics (IJCB), 2011 international joint conference on (pp. 1-7). IEEE.

    Google Scholar 

  27. Marshall, B.K., 2007. Tips for Avoiding Bad Authentication Challenge Questions. White Paper.

    Google Scholar 

  28. Masihuddin, M., Khan, B.U.I., Mattoo, M.M.U.I. and Olanrewaju, R.F., 2017. A survey on e-payment systems: elements, adoption, architecture, challenges and security concepts. Indian Journal of Science and Technology, 10(20), pp. 1-19.

    Article  Google Scholar 

  29. McQuiggan, S., McQuiggan, J., Sabourin, J. and Kosturko, L., 2015. Mobile learning: A handbook for developers, educators, and learners. John Wiley & Sons.

    Google Scholar 

  30. McWaters R. 2016. A Blueprint for Digital Identity. World Economic Forum.

    Google Scholar 

  31. Mehraj, T., Rasool, B., Khan, B.U.I., Baba, A. and Lone, A.G., 2015. Contemplation of effective security measures in access management from adoptability perspective. International Journal of Advanced Computer Science and Applications, 6(8), pp.188-200.

    Google Scholar 

  32. Meng, W., Wong, D.S., Furnell, S. and Zhou, J., 2015. Surveying the development of biometric user authentication on mobile phones. IEEE Communications Surveys & Tutorials, 17(3), pp.1268-1293.

    Article  Google Scholar 

  33. Mir, M.S., Suhaimi, M.B.A., Khan, B.U.I., Mattoo, M.M.U.I. and Olanrewaju, R.F., 2017. Critical Security Challenges in Cloud Computing Environment: An Appraisal. Journal of Theoretical & Applied Information Technology, 95(10), pp 2234-2248.

    Google Scholar 

  34. Narayanan, A. and Shmatikov, V., 2005, November. Fast dictionary attacks on passwords using time-space tradeoff. In Proceedings of the 12th ACM conference on Computer and communications security (pp. 364-372). ACM.

    Google Scholar 

  35. Nguyen, N.C., Bosch, O.J., Ong, F.Y., Seah, J.S., Succu, A., Nguyen, T.V. and Banson, K.E., 2016. A systemic approach to understand smartphone usage in Singapore. Systems Research and Behavioral Science, 33(3), pp.360-380.

    Article  Google Scholar 

  36. Ockenden W. AM - eBay suffers catastrophic data breach in hack attack 22/05/2014 [Online]. Abc.net.au. 2014. http://www.abc.net.au/am/content/2014/s4009539.htm [Accessed 30 April 2018].

  37. Olanrewaju, R.F., Khan, B.U.I., Baba, A., Mir, R.N. and Lone, S.A., 2016, July. RFDA: Reliable framework for data administration based on split-merge policy. In SAI Computing Conference (SAI), 2016 (pp. 545-552). IEEE.

    Google Scholar 

  38. Olanrewaju, R.F., Khan, B.U.I., Mattoo, M.M.U.I., Anwar, F., Nordin, A.N.B. and Mir, R.N., 2017a. Securing electronic transactions via payment gateways–a systematic review. International Journal of Internet Technology and Secured Transactions, 7(3), pp.245-269.

    Article  Google Scholar 

  39. Olanrewaju, R.F., Khan, B.U.I., Mattoo, M.M.U.I., Anwar, F., Nordin, A.N.B., Mir, R.N. and Noor, Z., 2017b. Adoption of Cloud Computing in Higher Learning Institutions: A Systematic Review. Indian Journal of Science and Technology, 10(36), pp.1-19.

    Article  Google Scholar 

  40. Osseiran, A., Monserrat, J.F. and Marsch, P. eds., 2016. 5G mobile and wireless communications technology. Cambridge University Press.

    Google Scholar 

  41. Pampori, B.R., Mehraj, T., Khan, B.U.I., Baba, A.M. and Najar, Z.A., 2018. Securely eradicating cellular dependency for e-banking applications. International Journal of Advanced Computer Science and Applications (IJACSA), 9(2), pp.385-398.

    Google Scholar 

  42. Pan, G., Sun, L., Wu, Z. and Lao, S., 2007. Eyeblink-based anti-spoofing in face recognition from a generic webcamera.

    Google Scholar 

  43. Ratha, N.K., Connell, J.H. and Bolle, R.M., 2001, June. An analysis of minutiae matching strength. In International Conference on Audio-and Video-Based Biometric Person Authentication (pp. 223-228). Springer, Berlin, Heidelberg.

    Google Scholar 

  44. Rathgeb, C. and Uhl, A., 2011. A survey on biometric cryptosystems and cancelable biometrics. EURASIP Journal on Information Security, 2011(1), p.3.

    Google Scholar 

  45. Reid, A.S., 2018. Financial Crime in the Twenty-First Century: The Rise of the Virtual Collar Criminal. In White Collar Crime and Risk (pp. 231-251). Palgrave Macmillan, London.

    Google Scholar 

  46. Ross, A.A., Nandakumar, K. and Jain, A.K., 2008. Handbook of biometrics. US: Springer.

    Google Scholar 

  47. Sadeghi, A.R., Schneider, T. and Wehrenberg, I., 2009, December. Efficient privacy-preserving face recognition. In International Conference on Information Security and Cryptology (pp. 229-244). Springer, Berlin, Heidelberg.

    Chapter  Google Scholar 

  48. Smith, D.F., Wiliem, A. and Lovell, B.C., 2015. Face recognition on consumer devices: Reflections on replay attacks. IEEE Transactions on Information Forensics and Security, 10(4), pp.736-745.

    Article  Google Scholar 

  49. Statista, Smartphone OS market share forecast 2014-2022 | Statistic, 2018. [Online]. Available: https://www.statista.com/statistics/272307/market-share-forecast-for-smartphone-operating-systems/. [Accessed: 30- April- 2018].

  50. Singh, A.K., Kumar, B., Dave, M., Ghrera, S.P. and Mohan, A., 2016. Digital image watermarking: techniques and emerging applications. In Handbook of research on modern cryptographic solutions for computer and cyber security (pp. 246-272). IGI Global.

    Google Scholar 

  51. Singh, A.K., Kumar, B., Singh, G. and Mohan, A. eds., 2017. Medical image watermarking: techniques and applications. Springer.

    Google Scholar 

  52. Téllez, J. and Zeadally, S., 2017. Mobile Payment Systems: Secure Network Architectures and Protocols. Springer.

    Google Scholar 

  53. Teo, C.C. and Neo, H.F., 2017, May. Behavioral Fingerprint Authentication: The Next Future. In Proceedings of the 9th International Conference on Bioinformatics and Biomedical Technology (pp. 1-5). ACM.

    Google Scholar 

  54. Yang, Y., Sun, J.S., Zhang, C. and Li, P., 2015, October. Retraining and Dynamic Privilege for Implicit Authentication Systems. In Mobile Ad Hoc and Sensor Systems (MASS), 2015 IEEE 12th International Conference on (pp. 163-171). IEEE.

    Google Scholar 

  55. Zhao, Z., Dong, Z. and Wang, Y., 2006. Security analysis of a password-based authentication protocol proposed to IEEE 1363. Theoretical Computer Science, 352(1-3), pp.280-287.

    Article  MathSciNet  Google Scholar 

Download references

Acknowledgments

This work was partially supported by Ministry of Higher Education Malaysia (Kementerian Pendidikan Tinggi) under Research Initiative Grant Scheme number: RIGS16-334-0498.

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2019 Springer Nature Switzerland AG

About this chapter

Check for updates. Verify currency and authenticity via CrossMark

Cite this chapter

Mehraj, T., Khan, B.U.I., Olanrewaju, R.F., Anwar, F., Jusoh, A.Z.B. (2019). An Adaptive and Viable Face Identification for Android Mobile Devices. In: Singh, A., Mohan, A. (eds) Handbook of Multimedia Information Security: Techniques and Applications. Springer, Cham. https://doi.org/10.1007/978-3-030-15887-3_13

Download citation

  • DOI: https://doi.org/10.1007/978-3-030-15887-3_13

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-15886-6

  • Online ISBN: 978-3-030-15887-3

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics