Advertisement

Cluster Computing

, Volume 19, Issue 1, pp 455–474 | Cite as

Continuous and transparent multimodal authentication: reviewing the state of the art

  • Abdulwahid Al Abdulwahid
  • Nathan Clarke
  • Ingo Stengel
  • Steven Furnell
  • Christoph Reich
Article

Abstract

Individuals, businesses and governments undertake an ever-growing range of activities online and via various Internet-enabled digital devices. Unfortunately, these activities, services, information and devices are the targets of cybercrimes. Verifying the user legitimacy to use/access a digital device or service has become of the utmost importance. Authentication is the frontline countermeasure of ensuring only the authorized user is granted access; however, it has historically suffered from a range of issues related to the security and usability of the approaches. They are also still mostly functioning at the point of entry and those performing sort of re-authentication executing it in an intrusive manner. Thus, it is apparent that a more innovative, convenient and secure user authentication solution is vital. This paper reviews the authentication methods along with the current use of authentication technologies, aiming at developing a current state-of-the-art and identifying the open problems to be tackled and available solutions to be adopted. It also investigates whether these authentication technologies have the capability to fill the gap between high security and user satisfaction. This is followed by a literature review of the existing research on continuous and transparent multimodal authentication. It concludes that providing users with adequate protection and convenience requires innovative robust authentication mechanisms to be utilized in a universal level. Ultimately, a potential federated biometric authentication solution is presented; however it needs to be developed and extensively evaluated, thus operating in a transparent, continuous and user-friendly manner.

Keywords

User authentication Authentication technologies Security Usability Transparent authentication Biometrics Continuous authentication 

References

  1. 1.
    Conrad, E., Misenar, S., Feldman, J.: Cissp Study Guide. Elsevier Inc., Burlington (2012)Google Scholar
  2. 2.
    Wood, H.M.: The use of passwords for controlling access to remote computer systems and services. In: Proceedings of the June 13–16, 1977, National Computer Conference (AFIPS ’77), pp. 27–33. ACM Press, New York, NY, USA (1977)Google Scholar
  3. 3.
    Zekri, L., Furnell, S.: Authentication based upon secret knowledge and its resilience to impostors. Adv. Netw. Commun. Eng. 3, 30–38 (2006)Google Scholar
  4. 4.
    O’Gorman, L.: Comparing passwords, tokens, and biometrics for user authentication. Proc. IEEE. 91, 2021–2040 (2003)CrossRefGoogle Scholar
  5. 5.
    Kurkovsky, S., Syta, E.: Digital natives and mobile phones: a survey of practices and attitudes about privacy and security. In: 2010 IEEE International Symposium on Technology and Society, pp. 441–449. IEEE (2010)Google Scholar
  6. 6.
    Symes, J.E., Clarke, N.L.: Security on mobile devices: a survey of users’ attitudes and opinions. Adv. Commun. Comput. Netw. Secur. 9, 59–68 (2012)Google Scholar
  7. 7.
    Crawford, H., Renaud, K.: Understanding user perceptions of transparent authentication on a mobile device. J. Trust Manag. 1, 1–28 (2014)CrossRefGoogle Scholar
  8. 8.
    CSID: Consumer survey: password habits, a study among American consumers. http://www.csid.com/wp-content/uploads/2012/09/CS_PasswordSurvey_FullReport_FINAL.pdf. Accessed 18 June 2013
  9. 9.
    Shankdhar, P.: 10 most popular password cracking tools. http://resources.infosecinstitute.com/10-popular-password-cracking-tools/. Accessed 30 Dec 2014
  10. 10.
    Clarke, N.: Transparent User Authentication: Biometrics, RFID and Behavioural Profiling. Springer, London (2011)CrossRefGoogle Scholar
  11. 11.
    Nelson, D., Reed, V., Walling, J.: Pictorial superiority effect. J. Exp. Psychol. Hum. Learn. Mem. 2, 523–528 (1976)CrossRefGoogle Scholar
  12. 12.
    Weiss, R., Luca, A. De: PassShapes: utilizing stroke based authentication to increase password memorability. In: Proceedings of the 5th Nordic Conference on n Human–Computer Interaction, pp. 18–22 (2008)Google Scholar
  13. 13.
    De Luca, A., Hang, A., Brudy, F., Lindner, C., Hussmann, H.: Touch me once and i know it’s you!: implicit authentication based on touch screen patterns. In: The SIGCHI Conference on Human Factors in Computing Systems, CHI 2012, pp. 987–996. Austin, TX, USA (2012)Google Scholar
  14. 14.
    Aviv, A.J., Gibson, K., Mossop, E., Blaze, M., Smith, J.M.: Smudge attacks on smartphone touch screens. In: Proceedings of the 4th USENIX Conference on Offensive technologies, WOOT’10 (2010)Google Scholar
  15. 15.
    Wiedenbeck, S., Waters, J., Birget, J.-C., Brodskiy, A., Memon, N.: Authentication using graphical passwords: effects of tolerance and image choice. In: Symposium on Usable Privacy and Security (SOUPS) 2005 (2005)Google Scholar
  16. 16.
    van Oorschot, P., Thorpe, J.: Exploiting predictability in click-based graphical passwords. J. Comput. Secur. 19, 669–702 (2011)Google Scholar
  17. 17.
    Charrau, D., Furnell, S., Dowland, P.: PassImages: an alternative method of user authentication. In: Proceedings of the 4th Annual ISOneWorld Conference and Convention. Las Vegas, USA (2005)Google Scholar
  18. 18.
    English, R., Poet, R.: Towards a metric for recognition-based graphical password security. In: 5th International Conference on Network and System Security (NSS), 2011, pp. 6–8 (2011)Google Scholar
  19. 19.
    Microsoft: features of Windows 8.1—Microsoft Windows. http://windows.microsoft.com/en-gb/windows-8/features#personalize=startscreen. Accessed 08 Nov 2014
  20. 20.
    Passfaces: passfaces personal version 1.0. http://www.passfaces.com/personal/support/helpmanual.htm. Accessed 05 May 2014
  21. 21.
    Ellis, H., Shepherd, J., Davies, G.: Identification of familiar and unfamiliar faces from internal and external features: some implications for theories of face recognition. Perception 8, 431–439 (1979)CrossRefGoogle Scholar
  22. 22.
    Aloul, F., Zahidi, S., El-Hajj, W.: Two factor authentication using mobile phones. In: 2009 IEEE/ACS International Conference on Computer Systems and Applications, pp. 641–644. IEEE (2009)Google Scholar
  23. 23.
    HSBC Bank plc: Secure key: two-factor authentication \(\vert \) HSBC UK. http://www.hsbc.co.uk/1/2/customer-support/online-banking-security/secure-key. Accessed 05 Nov 2014
  24. 24.
    Google: install google authenticator. https://support.google.com/accounts/answer/1066447?hl=en. Accessed 05 Nov 2014
  25. 25.
    Furnell, S.M., Katsikas, S., Lopez, J., Patel, A.: Securing Information and Communications Systems: Principles, Technologies, and Applications. Artech House, Norwood (2008)MATHGoogle Scholar
  26. 26.
    BBC: security firm RSA offers to replace SecurID tokens. http://www.bbc.co.uk/news/technology-13681566. Accessed 05 May 2014
  27. 27.
    Nanavati, S., Thieme, M., Nanavati, R.: Biometrics: Identity Verification in a Networked World. Wiley, New York (2002)Google Scholar
  28. 28.
    Jain, A.K., Flynn, P., Ross, A.A.: Handbook of Biometrics. Springer, New York (2008)CrossRefGoogle Scholar
  29. 29.
    Schouten, B., Jacobs, B.: Biometrics and their use in e-passports. Image Vis. Comput. 27, 305–312 (2009)CrossRefGoogle Scholar
  30. 30.
    Clarke, N., Furnell, S.: Biometrics—the promise versus the practice. Comput. Fraud Secur. 9, 12–16 (2005)CrossRefGoogle Scholar
  31. 31.
    Goode Intelligence: Mobile Phone Biometric Security—Analysis and Forecasts 2011–2015. http://www.goodeintelligence.com/report-store/view/mobile-phone-biometric-security-analysis-andforecasts-20112015. Accessed 08 Jan 2015
  32. 32.
    FBI: next generation identification. http://www.fbi.gov/about-us/cjis/fingerprints_biometrics/ngi. Accessed 04 June 2014
  33. 33.
    National Science and Technology Council: The National Biometrics Challenge 2011. http://biometrics.gov/Documents/BiometricsChallenge2011_protected.pdf. Accessed 03 June 2014
  34. 34.
    European Central Bank: Recommendations for the Security of Internet Payments—Final Version After Public Consultation, Germany (2013)Google Scholar
  35. 35.
    Federal Financial Institutions Examination Council: Authentication in an Internet Banking Environment. http://digitallibrary.kcci.com.pk/handle/32417747/701. Accessed 08 May 2014
  36. 36.
    NatWest: NatWest personal banking \(\vert \) online banking. http://www.natwest.com/personal/online-banking/g1/banking-safely-online/card-reader.ashx. Accessed 08 Nov 2014
  37. 37.
    Lloyds Bank: Lloyds Bank—internet banking—how to log on—help logging on. http://www.lloydsbank.com/online-banking/logging-on.asp?WT.ac=SNOBLO1012. Accessed 08 Nov 2014
  38. 38.
    Samba financial group: SambaOnline banking—ways to bank. http://www.samba.com/en/personal-banking/ways-to-bank/samba-online.html. Accessed 08 Nov 2014
  39. 39.
    White, C.: Windows 8.1 will focus on biometrics for authentication. http://www.neowin.net/news/windows-81-will-focus-on-biometrics-for-authentication. Accessed 24 March 2014
  40. 40.
    O’Boyle, B.: How does the Samsung Galaxy S5 fingerprint scanner work? http://www.pocket-lint.com/news/127605-how-does-the-samsung-galaxy-s5-fingerprint-scanner-work. Accessed 13 June 2014
  41. 41.
    Samsung: Samsung Galaxy S5 (Black)—review, specs & features—Samsung UK. http://www.samsung.com/uk/consumer/mobile-devices/smartphones/android/SM-G900FZKABTU. Accessed 08 Nov 2014
  42. 42.
    Mogull, R.: The iPhone 5s fingerprint reader: what you need to know. http://www.macworld.com/article/2048514/the-iphone-5s-fingerprint-reader-what-you-need-to-know.html. Accessed 13 June 2014
  43. 43.
    Apple: iPhone 5s—technical specifications. https://www.apple.com/uk/iphone-5s/specs/. Accessed 08 Nov 2014
  44. 44.
    IDC: smartphone OS market share 2014, 2013, 2012, and 2011. http://www.idc.com/prodserv/smartphone-os-market-share.jsp. Accessed 08 Jan 2015
  45. 45.
    Macworld: take the pain out of two-factor authentication with an app. http://www.macworld.com/article/2840979/take-the-pain-out-of-two-factor-authentication-with-an-app.html. Accessed 08 Jan 2015
  46. 46.
    Sandhu, S.: Single sign on concepts & protocols. https://www.sans.org/reading-room/whitepapers/authentication/single-sign-concepts-protocols-1352. Accessed 26 Mar 2014
  47. 47.
    Furnell, S.: Authenticating ourselves: will we ever escape the password? Netw. Secur. 2005, 8–13 (2005)CrossRefGoogle Scholar
  48. 48.
    Stihler, M., Santin, A.O., Marcon Jr., A.L., Fraga, J.D.S.: Integral federated identity management for cloud computing. In: 2012 5th International Conference on New Technologies, Mobility and Security (NTMS), pp. 1–5. IEEE (2012)Google Scholar
  49. 49.
    Cloud Security Alliance: Identity and access management implementation guidance. In: Cloud Security Alliance Security as a Service Implementation Guidance Version 1.0. pp. 1–43 (2012)Google Scholar
  50. 50.
    Madsen, P., Koga, Y., Takahashi, K.: Federated identity management for protecting users from ID theft. In: Proceedings of the 2005 Workshop on Digital identity management—DIM ’05, pp. 77–83. ACM Press, New York, NY, USA (2005)Google Scholar
  51. 51.
    Traore, I., Ahmed, A.A.E.: Continuous Authentication Using Biometrics: Data, Models, and Metrics. IGI Global, Hershey (2012)CrossRefGoogle Scholar
  52. 52.
    Umphress, D., Williams, G.: Identity verification through keyboard characteristics. Int. J. Man. Mach. Stud. 23, 263–273 (1985)CrossRefGoogle Scholar
  53. 53.
    Leggett, J., Williams, G.: Verifying identity via keystroke characteristics. Int. J. Man. Mach. Stud. 28, 67–76 (1988)CrossRefGoogle Scholar
  54. 54.
    Shepherd, S.: Continuous authentication by analysis of keyboard typing characteristics. In: European Convention on Security and Detection, 1995, pp. 111–114. IET, Brighton (1995)Google Scholar
  55. 55.
    Mahar, D., Napier, R., Wagner, M., Laverty, W., Henderson, R., Hiron, M.: Optimizing digraph-latency based biometric typist verification systems: inter and intra typist differences in digraph latency distributions. Int. J. Hum. Comput. Stud. 43, 579–592 (1995)CrossRefGoogle Scholar
  56. 56.
    Furnell, S.M., Morrissey, J.P., Sanders, P.W., Stockel, C.T.: Applications of keystroke analysis for improved login security and continuous user authentication. Information Systems Security, pp. 283–294. Chapman & Hall, Ltd., London (1996)CrossRefGoogle Scholar
  57. 57.
    Monrose, F., Rubin, A.D.: Keystroke dynamics as a biometric for authentication. Future Gener. Comput. Syst. 16, 351–359 (2000)CrossRefGoogle Scholar
  58. 58.
    Dowland, P.S., Singh, H., Furnell, S.M.: A preliminary investigation of user authentication using continuous keystroke analysis. In: 8th IFIP Annual Working Conference on Information Security Management and Small System Security (2001)Google Scholar
  59. 59.
    Bergadano, F., Gunetti, D., Picardi, C.: User authentication through keystroke dynamics. ACM Trans. Inf. Syst. Secur. 5, 367–397 (2002)CrossRefGoogle Scholar
  60. 60.
    Gunetti, D., Picardi, C.: Keystroke analysis of free text. ACM Trans. Inf. Syst. Secur. 8, 312–347 (2005)CrossRefMATHGoogle Scholar
  61. 61.
    Hempstalk, K.: Continuous typist verification using machine learning, PhD Thesis, The University of Waikato (2009)Google Scholar
  62. 62.
    Hossain, M., Balagani, K.S., Phoha, V.V.: New impostor score based rejection methods for continuous keystroke verification with weak templates. In: 2012 IEEE Fifth International Conference on Biometrics: Theory, Applications and Systems (BTAS), pp. 251–258 (2012)Google Scholar
  63. 63.
    Marsters, J.: Keystroke dynamics as a biometric. University of Southampton (2009)Google Scholar
  64. 64.
    Messerman, A., Mustafic, T., Camtepe, S.A., Albayrak, S.: Continuous and non-intrusive identity verification in real-time environments based on free-text keystroke dynamics. In: 2011 International Joint Conference on Biometrics Compendium, IEEE Biometrics (IJCB), pp. 1–8. IEEE (2011)Google Scholar
  65. 65.
    Obaidat, M.S., Sadoun, B.: Verification of computer users using keystroke dynamics. IEEE Trans. Syst. Man. Cybern. B. Cybern. 27, 261–269 (1997)CrossRefGoogle Scholar
  66. 66.
    Roth, J., Liu, X., Metaxas, D.: On continuous user authentication via typing behavior. IEEE Trans. IMAGE Process. 23, 4611–4624 (2014)MathSciNetCrossRefGoogle Scholar
  67. 67.
    Gamboa, H., Fred, A.: A behavioral biometric system based on human–computer interaction. In: Defense and Security, pp. 381–392. International Society for Optics and Photonics (2004)Google Scholar
  68. 68.
    Pusara, M., Brodley, C.E.: User re-authentication via mouse movements. In: Proceedings of the 2004 ACM workshop on Visualization and data mining for computer security—VizSEC/DMSEC ’04, pp. 1–8. ACM Press, New York, NY, USA (2004)Google Scholar
  69. 69.
    Ahmed, A.A.E., Traore, I.: A new biometric technology based on mouse dynamics. IEEE Trans. dependable Secur. Comput. 4, 165–179 (2007)CrossRefGoogle Scholar
  70. 70.
    Aksari, Y., Artuner, H.: Active authentication by mouse movements. In: ISCIS 2009, 24th International Symposium on Computer and Information Sciences, 2009, pp. 571–574. IEEE (2009)Google Scholar
  71. 71.
    Shen, C., Cai, Z., Guan, X., Huilan, I., Du, J.: Feature analysis of mouse dynamics in identity authentication and monitoring. In: IEEE International Conference on Communications, 2009, ICC ’09, pp. 1–5 (2009)Google Scholar
  72. 72.
    Zheng, N., Paloski, A., Wang, H.: An efficient user verification system via mouse movements. In: Proceedings of the 18th ACM Conference on Computer and Communications Security, pp. 139–150. ACM, New York, NY, USA (2011)Google Scholar
  73. 73.
    Jorgensen, Z., Yu, T.: On mouse dynamics as a behavioral biometric for authentication. In: Proceedings of the 6th ACM Symposium on Information. Computer and Communications Security, pp. 476–482. ACM, New York, NY, USA (2011)Google Scholar
  74. 74.
    Lin, C., Chang, C., Liang, D.: A new non-intrusive authentication approach for data protection based on mouse dynamics. In: 2012 International Symposium on Biometrics and Security Technologies, pp. 9–14. IEEE (2012)Google Scholar
  75. 75.
    Feher, C., Elovici, Y., Moskovitch, R., Rokach, L., Schclar, A.: User identity verification via mouse dynamics. Inf. Sci. (NY) 201, 19–36 (2012)CrossRefGoogle Scholar
  76. 76.
    Mondal, S., Bours, P.: Continuous authentication using mouse dynamics. In: 2013 International Conference of the Biometrics Special Interest Group (BIOSIG), pp. 1–12. IEEE (2013)Google Scholar
  77. 77.
    Stanic, M.: Continuous user verification based on behavioral biometrics using mouse dynamics. In: Proceedings of the ITI 2013 35th International Conference on Information Technology Interfaces, pp. 251–256. IEEE, Cavtat, Croatia (2013)Google Scholar
  78. 78.
    Clarke, N.L., Mekala, A.R.: The application of signature recognition to transparent handwriting verification for mobile devices. Inf. Manag. Comput. Secur. 15, 214–225 (2007)Google Scholar
  79. 79.
    Kale, A., Rajagopalan, A.N., Cuntoor, N., Kruger, V.: Gait-based recognition of humans using continuous HMMs. In: Proceedings of the Fifth IEEE International Conference on Automatic Face and Gesture Recognition (FGRí02), pp. 1–6. IEEE (2002)Google Scholar
  80. 80.
    Morris, S.: A shoe-integrated sensor system for wireless gait analysis and real-time therapeutic feedback. University of Southampton (2004)Google Scholar
  81. 81.
    Mäntyjärvi, J., Lindholm, M., Vildjiounaite, E., Mäkelä, S.-M., Ailisto, H.: Identifying users of portable devices from gait pattern with accelerometers. In: Proceedings. (ICASSP ’05). IEEE International Conference on Acoustics, Speech, and Signal Processing, 2005, pp. 973–976. IEEE (2005)Google Scholar
  82. 82.
    Gafurov, D., Snekkenes, E.: Gait recognition using wearable motion recording sensors. EURASIP J. Adv. Signal Process. 2009, 415817 (2009)CrossRefMATHGoogle Scholar
  83. 83.
    Derawi, M.O., Gafurov, D., Bours, P.: Towards continuous authentication based on gait using wearable motion recording sensors. In: Traore, I., Ahmed, A.A.E. (eds.) Continuous Authentication Using Biometrics: Data, Models, and Metrics, pp. 170–190. IGI Global, Hershey (2012)CrossRefGoogle Scholar
  84. 84.
    Juefei-Xu, F., Bhagavatula, C., Jaech, A., Prasad, U., Savvides, M.: Gait-id on the move: pace independent human identification using cell phone accelerometer dynamics. In: 2012 IEEE Fifth International Conference on Biometrics: Theory. Applications and Systems (BTAS), pp. 8–15. IEEE, Arlington, VA (2012)Google Scholar
  85. 85.
    Nickel, C., Wirtl, T., Busch, C.: Authentication of smartphone users based on the way they walk using k-NN algorithm. In: 2012 Eighth International Conference on Intelligent Information Hiding and Multimedia Signal Processing, pp. 16–20. IEEE (2012)Google Scholar
  86. 86.
    Lu, H., Huang, J., Saha, T., Nachman, L.: Unobtrusive gait verification for mobile phones. In: Proceedings of the 2014 ACM International Symposium on Wearable Computers—ISWC ’14. pp. 91–98. ACM Press, New York, NY, USA (2014)Google Scholar
  87. 87.
    Tanviruzzaman, M., Ahamed, S.I.: Your phone knows you: almost transparent authentication for smartphones. In: 2014 IEEE 38th Annual Computer Software and Applications Conference, pp. 374–383. IEEE (2014)Google Scholar
  88. 88.
    Woo, R.H., Park, A., Hazen, T.J.: The MIT mobile device speaker verification corpus: data collection and preliminary experiments. In: IEEE Odyssey 2006: The Speaker and Language Recognition Workshop, 2006, pp. 1–6. IEEE (2006)Google Scholar
  89. 89.
    Kunz, M., Kasper, K., Reininger, H., Möbius, M., Ohms, J.: Continuous speaker verification in realtime. In: Proceedings of the Special Interest Group on Biometrics and Electronic Signatures, BIOSIG, vol. 2011, pp. 79–88 (2011)Google Scholar
  90. 90.
    Martucci, L.A., Zuccato, A., Smeets, B., Habib, S.M., Johansson, T., Shahmehri, N.: Privacy, security and trust in cloud computing: the perspective of the telecommunication industry. In: 9th International Conference on Ubiquitous Intelligence and Computing and 9th International Conference on Autonomic and Trusted Computing (UIC/ATC), 2012, pp. 627–632. IEEE (2012)Google Scholar
  91. 91.
    Abdullah, M., Bashier, H., Sayeed, S., Yusof, I., Azman, A., Ibrahim, S.Z., Liew, T.H.: Answering incoming call for implicit authentication using smartphone. J. Theor. Appl. Inf. Technol. 61, 193–199 (2014)Google Scholar
  92. 92.
    Aupy, A., Clarke, N.: User authentication by service utilisation profiling. In: Proceedings of the ISOneWorld 2005. Las Vegas, USA (2005)Google Scholar
  93. 93.
    Yazji, S., Chen, X., Dick, R.P., Scheuermann, P.: Implicit user re-authentication for mobile devices. Ubiquitous Intelligence and Computing, pp. 1–15. Springer, New York (2009)Google Scholar
  94. 94.
    Jakobsson, M., Shi, E., Golle, P., Chow, R.: Implicit authentication for mobile devices. In: The 4th USENIX Conference on Hot Topics in Security, HotSec’09 (2009)Google Scholar
  95. 95.
    Saevanee, H., Clarke, N., Furnell, S.: SMS linguistic profiling authentication on mobile device. In: 2011 5th International Conference on Network and System Security, pp. 224–228. IEEE (2011)Google Scholar
  96. 96.
    Li, F., Wheeler, R., Clarke, N.: An evaluation of behavioural profiling on mobile devices. In: Proceedings of Second International Conference on HAS, vol. 8533, pp. 330–339 (2014)Google Scholar
  97. 97.
    Klosterman, A., Ganger, G.: Secure continuous biometric-enhanced authentication. In: Technical Report CMU-CS-00-134, Carnegie Mellon University (2000)Google Scholar
  98. 98.
    Liu, X., Chen, T.: Video-based face recognition using adaptive hidden markov models. In: Proceedings of the 2003 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR’03). IEEE (2003)Google Scholar
  99. 99.
    Janakiraman, R., Kumar, S., Sim, T.: Using continuous face verification to improve desktop security. In: 2005 Seventh IEEE Workshops on Applications of Computer Vision (WACV/MOTION’05), vol. 1, pp. 501–507. IEEE (2005)Google Scholar
  100. 100.
    Clarke, N., Karatzouni, S., Furnell, S.: Transparent facial recognition for mobile devices. In: Proceedings of the 7th Security Conference. Las Vegas, USA (2008)Google Scholar
  101. 101.
    Xiao, Q., Yang, X.-D.: Facial recognition in uncontrolled conditions for information security. EURASIP J. Adv. Signal Process. 2010, 1–10 (2010)MathSciNetMATHGoogle Scholar
  102. 102.
    Hurley, D., Nixon, M., Carter, J.: Automatic ear recognition by force field transformations. In: IEE Colloquium on Visual Biometrics, pp. 2–6. IET, London (2000)Google Scholar
  103. 103.
    Rodwell, P.M.: Non-intrusive subscriber authentication for next generation mobile communication systems, PhD Thesis, University of Plymouth (2006)Google Scholar
  104. 104.
    Islam, S., Davies, R., Mian, A.S., Bennamoun, M.: A fast and fully automatic ear recognition approach based on 3D local surface features. Advanced Concepts for Intelligent Vision Systems. Lecture Notes in Computer Science, vol. 5259, pp. 1081–1092. Springer, Berlin (2008)CrossRefGoogle Scholar
  105. 105.
    Fahmi, P.N.A., Kodirov, E., Choi, D.-J., Lee, G.-S., Mohd Fikri Azli, A., Sayeed, S.: Implicit authentication based on ear shape biometrics using smartphone camera during a call. In: 2012 IEEE International Conference on Systems, Man, and Cybernetics (SMC), pp. 2272–2276. IEEE (2012)Google Scholar
  106. 106.
    Feng, T., Liu, Z., Kwon, K.-A., Shi, W., Carbunar, B., Jiang, Y., Nguyen, N.: Continuous mobile authentication using touchscreen gestures. In: 2012 IEEE Conference on Technologies for Homeland Security (HST), pp. 451–456. IEEE (2012)Google Scholar
  107. 107.
    Koundinya, P., Theril, S., Feng, T., Prakash, V., Bao, J., Shi, W.: Multi resolution touch panel with built-in fingerprint sensing support. In: Design, Automation & Test in Europe Conference & Exhibition (DATE), 2014, pp. 1–6. IEEE Conference Publications, New Jersey (2014)Google Scholar
  108. 108.
    Kisku, D.R., Gupta, P., Sing, J.K., Tistarelli, M., Hwang, C.J.: Low level multispectral palmprint image fusion for large scale biometrics authentication. In: Traore, I., Ahmed, A.A.E. (eds.) Continuous Authentication Using Biometrics: Data, Models, and Metrics, pp. 89–104. IGI Global, Hershey (2012)CrossRefGoogle Scholar
  109. 109.
    Wildes, R.: Iris recognition: an emerging biometric technology. Proc. IEEE. 85, 1348–1363 (1997)CrossRefGoogle Scholar
  110. 110.
    Matey, J.R., Naroditsky, O., Hanna, K., Kolczynski, R., LoIacono, D.J., Mangru, S., Tinker, M., Zappia, T.M., Zhao, W.Y.: Iris on the move: acquisition of images for iris recognition in less constrained environments. Proc. IEEE. 94, 1936–1947 (2006)CrossRefGoogle Scholar
  111. 111.
    Proença, H., Alexandre, L.: Iris segmentation methodology for non-cooperative recognition. IEE Proc. Vis. Image Signal Process. 153, 199–205 (2006)CrossRefGoogle Scholar
  112. 112.
    Du, Y., Arslanturk, E., Zhou, Z., Belcher, C.: Video-based noncooperative iris image segmentation. IEEE Trans. Syst. Man, Cybern. B Cybern. 41, 64–74 (2011)CrossRefGoogle Scholar
  113. 113.
    Yang, K., Du, E.: A multi-stage approach for non-cooperative iris recognition. In: 2011 IEEE International Conference on Systems, Man, and Cybernetics (SMC), pp. 3386–3391. IEEE (2011)Google Scholar
  114. 114.
    Chen, R., Lin, X., Ding, T.: Liveness detection for iris recognition using multispectral images. Pattern Recognit. Lett. 33, 1513–1519 (2012)CrossRefGoogle Scholar
  115. 115.
    Mock, K., Hoanca, B., Weaver, J., Milton, M.: Real-time continuous iris recognition for authentication using an eye tracker. In: Proceedings of the 2012 ACM Conference on Computer and Communications Security, pp. 1007–1009. ACM (2012)Google Scholar
  116. 116.
    Sui, Y., Zou, X., Du, E.Y., Li, F.: Secure and privacy-preserving biometrics based active authentication. In: 2012 IEEE International Conference on Systems, Man, and Cybernetics (SMC), pp. 1291–1296. IEEE (2012)Google Scholar
  117. 117.
    Jain, A., Nandakumar, K., Ross, A.: Score normalization in multimodal biometric systems. Pattern Recognit. 38, 2270–2285 (2005)CrossRefGoogle Scholar
  118. 118.
    Ross, A., Nandakumar, K., Jain, A.: Handbook of Multibiometrics. Springer, New York (2006)Google Scholar
  119. 119.
    De Oliveira, A.E., Henrique Matos Bezerra Motta, G., Vidal Batista, L.: A multibiometric access control architecture for continuous authentication. In: 2010 IEEE International Conference on Intelligence and Security Informatics, pp. 171–171. IEEE (2010)Google Scholar
  120. 120.
    Sim, T., Zhang, S., Janakiraman, R., Kumar, S.: Continuous verification using multimodal biometrics. IEEE Trans. Pattern Anal. Mach. Intell. 29, 687–700 (2007)CrossRefGoogle Scholar
  121. 121.
    Azzini, A., Marrara, S.: Impostor users discovery using a multimodal biometric continuous authentication fuzzy system. Knowledge-Based Intell. Inf. Eng. Syst. 5178, 371–378 (2008)Google Scholar
  122. 122.
    De Oliveira, A.E., Motta, G.H.M.B.: A security API for multimodal multi-biometric continuous authentication. In: 2011 Seventh International Conference on Computational Intelligence and Security, pp. 988–992. IEEE (2011)Google Scholar
  123. 123.
    Tsatsoulis, P.D., Jaech, A., Batie, R., Savvides, M.: Multimodal biometric hand-off for robust unobtrusive continuous biometric authentication. In: Traore, I., Ahmed, A.A.E. (eds.) Continuous Authentication Using Biometrics: Data, Models, and Metrics, pp. 68–88. IGI Global, Hershey (2012)CrossRefGoogle Scholar
  124. 124.
    Kwang, G., Yap, R.H., Sim, T., Ramnath, R.: A usability study of continuous biometrics authentication. In: Tistarelli, M., Nixon, M.S. (eds.) Proceedings of the Third International Conference on Advances in Biometrics, pp. 828–837. Springer, Berlin (2009)Google Scholar
  125. 125.
    Ahmed, A., Traore, I.: Anomaly intrusion detection based on biometrics. In: Proceedings of the 2005 IEEE Workshop on Information Assurance and Security, pp. 452–453. IEEE (2005)Google Scholar
  126. 126.
    Pusara, M.: An Examination of User Behavior for User Re-authentication. ProQuest, Ann Arbor (2007)Google Scholar
  127. 127.
    Bailey, K.O., Okolica, J.S., Peterson, G.L.: User identification and authentication using multi-modal behavioral biometrics. Comput. Secur. 43, 77–89 (2014)CrossRefGoogle Scholar
  128. 128.
    Vildjiounaite, E., Mäkelä, S., Lindholm, M., Riihimäki, R.: Unobtrusive multimodal biometrics for ensuring privacy and information security with personal devices. In: Proceedings of the 4th International Conference on Pervasive Computing, pp. 187–201. Springer, Berlin (2006)Google Scholar
  129. 129.
    Li, F., Clarke, N., Papadaki, M., Dowland, P.: Behaviour profiling for transparent authentication for mobile devices. In: the 10th European Conference on Information Warfare and Security (ECIW 2011), pp. 307–314, Tallinn, Estonia (2011)Google Scholar
  130. 130.
    Crawford, H., Renaud, K., Storer, T.: A framework for continuous, transparent mobile device authentication. Comput. Secur. 39, 127–136 (2013)CrossRefGoogle Scholar
  131. 131.
    Saevanee, H., Clarke, N., Furnell, S., Biscione, V.: Text-based active authentication for mobile devices. IFIP Adv. Inf. Commun. Technol. ICT Syst. Secur. Priv. Prot. 428, 99–112 (2014)CrossRefGoogle Scholar
  132. 132.
    Carrillo, C.: Continuous Biometric Authentication for Authorized Aircraft Personnel: A Proposed Design. Naval Postgraduate School, Monterey (2003)Google Scholar
  133. 133.
    Clarke, N., Furnell, S.: A composite user authentication architecture for mobile devices. J. Inf. Warf. 5, 11–29 (2006)Google Scholar
  134. 134.
    Asha, S., Chellappan, C.: Authentication of e-learners using multimodal biometric technology. In: International Symposium on Biometrics and Security Technologies, 2008, ISBAST 2008, pp. 1–6. IEEE (2008)Google Scholar
  135. 135.
    Muaaz, M.: A transparent and continuous biometric authentication framework for user-friendly secure mobile environments. In: The 2013 ACM International Joint Conference on Pervasive and Ubiquitous Computing (UbiComp 2013 Adjunct), pp. 4–7. ACM, Zurich, Switzerland (2013)Google Scholar
  136. 136.
    Altinok, A., Turk, M.: Temporal integration for continuous multimodal biometrics. In: Multimodal User Authentication (2003)Google Scholar
  137. 137.
    Kang, H.-B., Ju, M.-H.: Multi-modal feature integration for secure authentication. In: Huang, D.-S., Li, K., Irwin, G.W. (eds.) Proceedings of the 2006 International Conference on Intelligent Computing, pp. 1191–1200. Springer, Berlin (2006)Google Scholar
  138. 138.
    Ojala, S., Keinanen, J., Skytta, J.: Wearable authentication device for transparent login in nomadic applications environment. In: 2nd International Conference on Signals, Circuits and Systems, pp. 1–6 (2008)Google Scholar
  139. 139.
    Clarke, N., Karatzouni, S., Furnell, S.: Flexible and transparent user authentication for mobile devices. In: Gritzalis, D., Lopez, J. (eds.) Emerging Challenges for Security, Privacy and Trust, 24th IFIP TC 11 International Information Security Conference, SEC 2009, pp. 1–12. Springer, Pafos, Cyprus (2009)Google Scholar
  140. 140.
    Soltane, M., Doghmane, N., Guersi, N.: Face and speech based multi-modal biometric authentication. Int. J. Adv. Sci. Technol. 21, 41–56 (2010)Google Scholar
  141. 141.
    Niinuma, K., Park, U., Jain, A.K.: Soft biometric traits for continuous user authentication. IEEE Trans. Inf. Forensics Secur. 5, 771–780 (2010)CrossRefGoogle Scholar
  142. 142.
    Tsai, P., Khan, M.K., Pan, J., Liao, B.: Interactive artificial bee colony supported passive continuous authentication system. IEEE Syst. J. IEEE Biom. Compend. 8, 395–405 (2014)CrossRefGoogle Scholar
  143. 143.
    Khan, M.K., Tsai, P.-W., Pan, J.-S., Liao, B.-Y.: Biometric driven initiative system for passive continuous authentication. In: 7th International Conference on Information Assurance and Security (IAS), 2011, pp. 139–144. IEEE (2011)Google Scholar
  144. 144.
    Chowdhury, M., Light, J., McIver, W.: A framework for continuous authentication in ubiquitous environments. In: Sixth International Conference on Wireless Communication and Sensor Networks (WCSN), pp. 1–6. IEEE Press (2010)Google Scholar
  145. 145.
    Riva, O., Qin, C., Strauss, K., Lymberopoulos, D.: Progressive authentication: deciding when to authenticate on mobile phones. In: The 21st USENIX Security Symposium (2012)Google Scholar
  146. 146.
    Hocking, C.G., Furnell, S.M., Clarke, N.L., Reynolds, P.L.: Co-operative user identity verification using an Authentication Aura. Comput. Secur. 39, 486–502 (2013)CrossRefGoogle Scholar
  147. 147.
    Traore, I., Woungang, I., Obaidat, M.S., Nakkabi, Y., Lai, I.: Combining mouse and keystroke dynamics biometrics for risk-based authentication in web environments. In: 2012 Fourth International Conference on Digital Home, pp. 138–145. IEEE (2012)Google Scholar
  148. 148.
    Ceccarelli, A., Montecchi, L., Brancati, F., Lollini, P., Marguglio, A., Bondavalli, A.: Continuous and transparent user identity verification for secure internet services. IEEE Trans. Dependable Secur. Comput. 12, 270–283 (2014)Google Scholar
  149. 149.
  150. 150.
    Al Abdulwahid, A., Clarke, N., Furnell, S., Stengel, I.: A conceptual model for federated authentication in the cloud. In: Proceedings of the 11th Australian Information Security Management Conference (AISM2013), pp. 1–11. Edith Cowan University, Perth, Western Australia (2013)Google Scholar

Copyright information

© Springer Science+Business Media New York 2015

Authors and Affiliations

  • Abdulwahid Al Abdulwahid
    • 1
    • 2
  • Nathan Clarke
    • 1
  • Ingo Stengel
    • 1
  • Steven Furnell
    • 1
  • Christoph Reich
    • 3
  1. 1.Centre for Security, Communications and Network ResearchPlymouth UniversityPlymouthUK
  2. 2.Computer Science and Engineering DepartmentJubail University CollegeJubail Industrial CityKingdom of Saudi Arabia
  3. 3.Institute for Cloud Computing and IT-SecurityFurtwangen University of Applied ScienceFurtwangenGermany

Personalised recommendations