Behavioral, Cognitive and Virtual Biometrics

  • Roman V. Yampolskiy


This chapter presents an overview and classification of security approaches based on computer analysis of human behavior. Overview of different methodologies is followed by an analysis of achieved accuracy rates, required equipment and prospects for future improvements. In particular the following broad categories of behavior-based authentication mechanisms are examined: Behavioral Biometrics (Authorship based, Human–Computer Interaction based, Motor Skill, and Purely Behavioral), Behavioral Passwords (syntactic, semantic, one-time methods and visual memory based), Biosignals (cognitive and semi-controllable biometrics) and Virtual Biometrics (representations of users in virtual worlds).


Intrusion Detection System Equal Error Rate Brain Computer Interface Behavioral Profile Biometric System 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


  1. 1.
    Angle, S., Bhagtani, R., Chheda, H.: Biometrics: a further echelon of security. In: First UAE International Conference on Biological and Medical Physics (2005) Google Scholar
  2. 2.
    Dugelay, J.-L., et al.: Recent advances in biometric person authentication. In: IEEE Int. Conf. on Acoustics Speech and Signal Processing (ICASSP), Special Session on Biometrics, Orlando, Florida (2002) Google Scholar
  3. 3.
    Lee, K., Park, H.: A new similarity measure based on intraclass statistics for biometric systems. ETRI J. 25(5), 401–406 (2003) Google Scholar
  4. 4.
    Cappelli, R., et al.: Performance evaluation of fingerprint verification systems. IEEE Trans. Pattern Anal. Mach. Intell. 28(1), 3–18 (2006) Google Scholar
  5. 5.
    Jain, A.K., Ross, A., Prabhakar, S.: An introduction to biometric recognition. In: IEEE Trans. Circuits Syst. Video Technol. (2004) Google Scholar
  6. 6.
    Bolle, R., et al.: Guide to Biometrics. Springer, Berlin (2003) Google Scholar
  7. 7.
    Jain, A.K., et al.: Biometrics: a grand challenge. In: International Conference on Pattern Recognition, Cambridge, UK (2004) Google Scholar
  8. 8.
    Uludag, U., et al.: Biometric cryptosystems: issues and challenges. Proc. IEEE 92(6) (2004) Google Scholar
  9. 9.
    Delac, K., Grgic, M.: A survey of biometric recognition methods. In: 46th International Symposium Electronics in Marine, ELMAR-2004, Zadar, Croatia (2004) Google Scholar
  10. 10.
    Ruggles, T.: Comparison of biometric techniques (2007). Available at:
  11. 11.
    Solayappan, N., Latifi, S.: A survey of unimodal biometric methods. In: Security and Management, Las Vegas, Nevada, USA (2006) Google Scholar
  12. 12. FAQ. BioPrivacy Initiative (2005). July 22, 2005. Available from:
  13. 13.
    Bromme, A.: A classification of biometric signatures. In: International Conference on Multimedia and Expo (ICME ’03) (2003) Google Scholar
  14. 14.
    Yampolskiy, R.V.: Human computer interaction based intrusion detection. In: 4th International Conference on Information Technology: New Generations (ITNG 2007), Las Vegas, Nevada, USA (2007) Google Scholar
  15. 15. FAQ’s and Definitions. International Biometric Group, LLC (2005). October 2, 2005. Available from:
  16. 16.
    Yampolskiy, R.V.: Indirect human–computer interaction-based biometrics for intrusion detection systems. In: The 41st Annual IEEE International Carnahan Conference on Security Technology (ICCST 2007), Ottawa, Canada (2007) Google Scholar
  17. 17.
    Denning, D.E.: An intrusion-detection model. In: IEEE Transactions on Software Engineering (1987) Google Scholar
  18. 18.
    Ilgun, K., Kemmerer, R.A., Porras, P.A.: State transition analysis: A rule-based intrusion detection approach. In: Software Engineering (1995) Google Scholar
  19. 19.
    Ghosh, A.K., Schwartzbard, A., Schatz, M.: Learning program behavior proles for intrusion detection. In: First USENIX Workshop on Intrusion Detection and Network Monitoring (1999) Google Scholar
  20. 20.
    Apap, F., et al.: Detecting malicious software by monitoring anomalous windows registry accesses. In: Fifth International Symposium on Recent Advances in Intrusion Detection, pp. 16–18 (2002) Google Scholar
  21. 21.
    Pennington, A.G., et al.: Storage-based intrusion detection: Watching storage activity for suspicious behavior. Carnegie Mellon University (2002) Google Scholar
  22. 22.
    Feng, H.H., et al.: Anomaly detection using call stack information. In: Proceedings of IEEE Symposium on Security and Privacy (2003) Google Scholar
  23. 23.
    Pusara, M., Brodley, C.E.: User re-authentication via mouse movements. In: VizSEC/DMSEC ’04: Proceedings of the ACM Workshop on Visualization and Data Mining for Computer Security. ACM, Washington (2004) Google Scholar
  24. 24.
    Garg, A., et al.: Profiling users in GUI based systems for masquerade detection. In: The 7th IEEE Information Assurance Workshop (IAWorkshop 2006), West Point, New York, USA (2006) Google Scholar
  25. 25.
    Yampolskiy, R.V.: Motor-skill based biometrics. In: Dhillon, G. (ed.) Assuring Business Processes, Proceedings of the 6th Annual Security Conference. Global Publishing, Las Vegas (2007) Google Scholar
  26. 26. Caslon-Analytics. October 2, 2005. Available from:
  27. 27.
    Jain, A.K., Bolle, R., Pankanti, S.: BIOMETRICS: Personal Identification in Networked Society. Kluwer Academic, Dordrecht (1999) Google Scholar
  28. 28.
    Adler, A., Youmaran, R., Loyka, S.: Towards a measure of biometric information (2006). Available at:
  29. 29.
    Koychev, I., Schwab, I.: Adaptation to drifting user’s interests. In: Proceedings of ECML2000 Workshop: Machine Learning in New Information Age, Barcelona, Spain (2000) Google Scholar
  30. 30.
    Tsymbal, A.: The problem of concept drift: definitions and related work. Technical Report TCD-CS-2004-15, Computer Science Department, Trinity College, Dublin, Ireland (2004) Google Scholar
  31. 31.
    Schuckers, S.A.C.: Spoofing and anti-spoofing measures. Information Security Technical Report (2002) Google Scholar
  32. 32.
    Yampolskiy, R.V., Govindaraju, V.: Behavioral biometrics: a survey and classification. Int. J. Biom. 1(1), 81–113 (2008) Google Scholar
  33. 33.
    Oursler, J.N., Price, M., Yampolskiy, R.V.: Parameterized generation of Avatar face dataset. In: 14th International Conference on Computer Games: AI, Animation, Mobile, Interactive Multimedia, Educational & Serious Games, Louisville, KY (2009) Google Scholar
  34. 34.
    Yampolskiy, R., Gavrilova, M.: Applying biometric principles to avatar recognition. In: International Conference on Cyberworlds (CW2010), Singapore, October 20–22 (2010) Google Scholar
  35. 35.
    Ajinal, S., Yampolskiy, R.V., Amara, N.E.B.: Authentification de Visages D’Avatar. In: Confere 2010 Symposium, Sousse, Tunisia, July 1–2 (2010) Google Scholar
  36. 36.
    Yampolskiy, R.V., Govindaraju, V.: Behavioral biometrics for verification and recognition of malicious software agents. In: Sensors, and Command, Control, Communications, and Intelligence (C3I) Technologies for Homeland Security and Homeland Defense VII. SPIE Defense and Security Symposium, Orlando, Florida, March 16–20 (2008) Google Scholar
  37. 37.
    D’Souza, D., Yampolskiy, R.V.: Avatar face detection analysis using an extended set of Haar-like features. In: Kentucky Academy of Science, Annual Meeting, Bowling Green, Kentucky, November 12–13 (2010) Google Scholar
  38. 38.
    Lyons, M., et al.: Avatar creation using automatic face recognition. In: ACM Multimedia 98, Bristol, England, Sept. 1998, pp. 427–434 (1998) Google Scholar
  39. 39.
    Yanushkevich, S., et al.: Image Pattern Recognition: Synthesis and Analysis in Biometrics. Machine Perception and Artificial Intelligence, vol. 67. World Scientific, Singapore (2007) Google Scholar
  40. 40.
    Brömme, A., Al-Zubi, S.: Multifactor biometric sketch authentication. In: BIOSIG, Darmstadt, Germany (2003) Google Scholar
  41. 41.
    Al-Zubi, S., Brömme, A., Tönnies, K.: Using an active shape structural model for biometric sketch recognition. In: DAGM, Magdeburg, Germany (2003) Google Scholar
  42. 42.
    Renaud, K.: Quantifying the quality of web authentication mechanisms. A usability perspective. J. Web Eng. (2003). Available at:
  43. 43.
    Westeyn, T., et al.: Biometric identification using song-based eye blink patterns. In: Human Computer Interaction International (HCII), Las Vegas, NV (2005) Google Scholar
  44. 44.
    Westeyn, T., Starner, T.: Recognizing song-based blink patterns: applications for restricted and universal access. In: Sixth IEEE International Conference on Automatic Face and Gesture Recognition (2004) Google Scholar
  45. 45.
    Hilas, C., Sahalos, J.: User profiling for fraud detection in telecommunication networks. In: 5th International Conference on Technology and Automation (ICTA 2005), Thessaloniki, Greece (2005) Google Scholar
  46. 46.
    Grosser, H., Britos, H., García-Martínez, R.: Detecting Fraud in Mobile Telephony Using Neural Networks. Lecture Notes in Artificial Intelligence. Springer, Berlin (2005) Google Scholar
  47. 47.
    Fawcett, T., Provost, F.: Adaptive fraud detection. In: Data Mining and Knowledge Discovery. Kluwer Academic, Dordrecht (1997) Google Scholar
  48. 48.
    Erzin, E., et al.: Multimodal person recognition for human-vehicle interaction. In: IEEE MultiMedia (April 2006) Google Scholar
  49. 49.
    Liu, A., Salvucci, D.: Modeling and prediction of human driver behavior. In: 9th HCI International Conference, New Orleans, LA (2001) Google Scholar
  50. 50.
    Oliver, N., Pentland, A.P.: Graphical models for driver behavior recognition in a SmartCar. In: Proceedings of the IEEE Intelligent Vehicles Symposium (2000) Google Scholar
  51. 51.
    Kuge, N., Yamamura, T., Shimoyama, O.: A driver behavior recognition method based on driver model framework. In: Society of Automotive Engineers Publication (1998) Google Scholar
  52. 52.
    Porwik, P., et al.: Biometric recognition system based on the motion of the human body gravity centre analysis. J. Med. Inform. Technol. 15 (2010) Google Scholar
  53. 53.
    Schonlau, M., et al.: Computer intrusion: detecting masquerades. Stat. Sci. 16(1), 1–17 (2001) MathSciNetGoogle Scholar
  54. 54.
    Maxion, R.A., Townsend, T.N.: Masquerade detection using truncated command lines. In: International Conference on Dependable Systems and Networks (DNS-02). IEEE Comput. Soc., Los Alamitos (2002) Google Scholar
  55. 55.
    Dao, V., Vemuri, V.: Profiling users in the UNIX OS environment. In: International ICSC Conference on Intelligent Systems and Applications, University of Wollongong, Australia (2000) Google Scholar
  56. 56.
    Brause, R., Langsdorf, T., Hepp, M.: Neural data mining for credit card fraud detection. In: Proceedings of the 11th IEEE International Conference on Tools with Artificial Intelligence (1999) Google Scholar
  57. 57.
    Pamudurthy, S., et al.: Dynamic approach for face recognition using digital image skin correlation. In: Audio- and Video-based Biometric Person Authentication (AVBPA), New York (2005) Google Scholar
  58. 58.
    Mainguet, J.-F.: Biometrics (2006). Available at:
  59. 59.
    Ito, A., et al.: Smile and laughter recognition using speech processing and face recognition from conversation video. In: Proceedings of the International Conference on Cyberworlds (2005) Google Scholar
  60. 60.
    Tsai, P., Hintz, T., Jan, T.: Facial behavior as behavior biometric? An empirical study. In: IEEE International Conference on Systems, Man and Cybernetics, Montreal, Quebec, October 7–10, pp. 3917–3922 (2007) Google Scholar
  61. 61.
    Benedikt, L., et al.: Assessing the uniqueness and permanence of facial actions for use in biometric applications. IEEE Trans. Syst. Man Cybern., Part A, Syst. Hum. 40(3), 449–460 (2010) Google Scholar
  62. 62.
    Stolfo, S.J., et al.: A behavior-based approach to securing email systems. In: Mathematical Methods, Models and Architectures for Computer Networks Security. LNCS, vol. 2776, pp. 57–81 (2003) Google Scholar
  63. 63.
    Stolfo, S.J., et al.: Combining behavior models to secure email systems. CU Tech Report (2003). Available at:
  64. 64.
    Vel, O.D., et al.: Mining email content for author identification forensics. SIGMOD Rec. 30(4), 55–64 (2001). Special Section on Data Mining for Intrusion Detection and Threat Analysis Google Scholar
  65. 65.
    Saevanee, H., Bhattarakosol, P.: Authenticating user using keystroke dynamics and finger pressure. In: 6th IEEE Consumer Communications and Networking Conference (CCNC), Las Vegas, NV, January 10–13, pp. 1–2 (2009) Google Scholar
  66. 66.
    Qian, G., Zhang, J., Kidane, A.: People identification using gait via floor pressure analysis IEEE Sens. J. 10(9), 1447–1460 (2010) Google Scholar
  67. 67.
    Addlesee, M., et al.: The ORL active floor. IEEE Pers. Commun. 35–41 (1997) Google Scholar
  68. 68.
    Jung, J., et al.: Dynamic-footprint based person identification using mat-type pressure sensor. In: International Conference of the IEEE Engineering in Medicine and Biology Society, pp. 2937–2940 (2003) Google Scholar
  69. 69.
    Pirttikangas, S., et al.: Footstep identification from pressure signals using hidden Markov models. In: Finnish Signal Processing Symposium, pp. 124–128 (2003) Google Scholar
  70. 70.
    Middleton, L., et al.: A floor sensor system for gait recognition. In: IEEE Workshop on Automatic Identification Advanced Technologies, pp. 171–176 (2005) Google Scholar
  71. 71.
    Yun, J., et al.: The user identification system using walking pattern over the ubiFloor. In: International Conference on Control, Automation, and Systems, pp. 1046–1050 (2003) Google Scholar
  72. 72.
    Orr, R.J., Abowd, G.D.: The smart floor: a mechanism for natural user identification and tracking. In: Conference on Human Factors in Computing Systems, pp. 275–276 (2000) Google Scholar
  73. 73.
    Yoon, J., Ryu, J., Woo, W.: User identification using user’s walking pattern over the ubiFloorII. In: International Conference on Computational Intelligence and Security, pp. 949–956 (2005) Google Scholar
  74. 74.
    Suutala, J., Röning, J.: Methods for person identification on a pressure-sensitive floor: Experiments with multiple classifiers and reject option. Inf. Fusion 9(1), 21–40 (2008) Google Scholar
  75. 75.
    Maeder, A.J., Fookes, C.B.: A visual attention approach to personal identification. In: Eighth Australian and New Zealand Intelligent Information Systems Conference, December 10–12 (2003) Google Scholar
  76. 76.
    Maeder, A.J., Fookes, C.B., Sridharan, S.: Gaze based user authentication for personal computer applications. In: International Symposium on Intelligent Multimedia, Video and Speech Processing, Hong Kong, China, October 20–22 (2004) Google Scholar
  77. 77.
    Kale, A., et al.: Identification of humans using gait. IEEE Trans. Image Proc. 13(9) (2004) Google Scholar
  78. 78.
    BenAbdelkader, C., Cutler, R., Davis, L.: Person identification using automatic height and stride estimation. In: IEEE International Conference on Pattern Recognition (2002) Google Scholar
  79. 79.
    Nixon, M.S., Carter, J.N.: On gait as a biometric: progress and prospects. In: EUSIPCO, Vienna (2004) Google Scholar
  80. 80.
    Kalyanaraman, S.: Biometric authentication systems. A report. 2006. Available at:
  81. 81.
    Yampolskiy, R.V.: Behavior based identification of network intruders. In: 19th Annual CSE Graduate Conference (Grad-Conf2006), Buffalo, NY (2006) Google Scholar
  82. 82.
    Yampolskiy, R.V., Govindaraju, V.: Use of behavioral biometrics in intrusion detection and online gaming. In: Biometric Technology for Human Identification III. SPIE Defense and Security Symposium, Orlando, Florida (2006) Google Scholar
  83. 83.
    Yampolskiy, R.V., Govindaraju, V.: Dissimilarity functions for behavior-based biometrics. In: Biometric Technology for Human Identification IV. SPIE Defense and Security Symposium, Orlando, Florida (2007) Google Scholar
  84. 84. Stats and analysis (2006). June 7, 2006. Available from:
  85. 85.
    Ramon, J., Jacobs, N.: Opponent modeling by analysing play. In: Proceedings of the Computers and Games workshop on Agents in Computer Games, Edmonton, Alberta, Canada (2002) Google Scholar
  86. 86.
    Jansen, A.R., Dowe, D.L., Farr, G.E.: Inductive inference of chess player strategy. In: Proceedings of the 6th Pacific Rim International Conference on Artificial Intelligence (PRICAI’2000) (2000) Google Scholar
  87. 87.
    Kauffman, J.A., et al.: Grip-pattern recognition for smart guns. In: 14th Annual Workshop on Circuits, Systems and Signal Processing (ProRISC), Veldhoven, The Netherlands (2003) Google Scholar
  88. 88.
    Veldhuis, R.N.J., et al.: Biometric verification based on grip-pattern recognition. In: Security, Steganography, and Watermarking of Multimedia Contents (2004) Google Scholar
  89. 89.
    Orozco, M., et al.: Automatic identification of participants in haptic systems. In: IEEE Instrumentation and Measurement Technology Conference, Ottawa, Canada (2005) Google Scholar
  90. 90.
    Orozco, M., et al.: Haptic-based biometrics: a feasibility study. In: IEEE Virtual Reality Conference, Alexandria, Virginia, USA (2006) Google Scholar
  91. 91.
    Trujillo, M.O., Shakra, I., Saddik, A.E.: Haptic: the new biometrics-embedded media to recognizing and quantifying human patterns. In: MULTIMEDIA ’05: Proceedings of the 13th Annual ACM International Conference on Multimedia, Hilton, Singapore. ACM, New York (2005) Google Scholar
  92. 92.
    Stoica, A.: Towards recognition of humans and their behaviors from space and airborne platforms: extracting the information in the dynamics of human shadows. In: Symposium on Bio-inspired Learning and Intelligent Systems for Security (BLISS ’08), Edinburgh, August 4–6, pp. 125–128 (2008) Google Scholar
  93. 93.
    Iwashita, Y., Stoica, A., Kurazume, R.: Person identification using shadow analysis. In: British Machine Vision Conference, September, pp. 35.1–35.10 (2010) Google Scholar
  94. 94.
    Ilonen, J.: Keystroke dynamics (2006). Available at:
  95. 95.
    Bella, S.D., Palmer, C.: Personal identifiers in musicians’ finger movement dynamics. J. Cogn. Neurosci. 18 (2006) Google Scholar
  96. 96.
    Gamboa, H., Fred, A.L.N., Jain, A.K.: Webbiometrics: User verification via web interaction. In: Biometrics Symposium, Baltimore, MD, September 11–13, pp. 1–6 (2007). Google Scholar
  97. 97.
    Shipilova, O.: Person recognition based on lip movements (2006). Available at:
  98. 98.
    Broun, C.C., et al.: Automatic speechreading with applications to speaker verification. In: Eurasip Journal on Applied Signal Processing, Special Issue on Joint Audio-Visual Speech Processing (2002) Google Scholar
  99. 99.
    Luettin, J., Thacker, N.A., Beet, S.W.: Speaker identification by lipreading. In: Proceedings of the 4th International Conference on Spoken Language Processing (ICSLP’96) (1996) Google Scholar
  100. 100.
    Wark, T., Thambiratnam, D., Sridharan, S.: Person authentication using lip information. In: Proceedings of IEEE 10th Annual Conference. Speech and Image Technologies for Computing and Telecommunications (1997) Google Scholar
  101. 101.
    Mason, J.S.D., et al.: Lip signatures for automatic person recognition. In: IEEE Workshop, MMSP (1999) Google Scholar
  102. 102.
    Jourlin, P., et al.: Acoustic-labial speaker verification. In: Pattern Recognition Letters (1997) Google Scholar
  103. 103.
    Mok, L., et al.: Person authentication using ASM based lip shape and intensity information. In: International Conference on Image Processing (2004) Google Scholar
  104. 104.
    Ahmed, A.A.E., Traore, I.: Detecting computer intrusions using behavioral biometrics. In: Third Annual Conference on Privacy, Security and Trust, St. Andrews, New Brunswick, Canada (2005) Google Scholar
  105. 105.
    Ahmed, A.A.E., Traore, I.: Anomaly intrusion detection based on biometrics. In: Workshop on Information Assurance, United States Military Academy, West Point, NY (2005) Google Scholar
  106. 106.
    Gamboa, H., Fred, V.-A.: A behavioral biometric system based on human–computer interaction. In: Proceedings of SPIE (2004) Google Scholar
  107. 107.
    Gamboa, H., Fred, A.: An identity authentication system based on human–computer interaction behaviour. In: Proc. of the 3rd Intl. Workshop on Pattern Recognition in Information Systems (2003) Google Scholar
  108. 108.
    Nishiuchi, N., Komatsu, S., Yamanaka, K.: A biometric identification using the motion of fingers. In: International Conference on Biometrics and Kansei Engineering, Cieszyn, Poland, June 25–28, pp. 22–27 (2009) Google Scholar
  109. 109.
    Lyu, S., Rockmore, D., Farid, H.: A digital technique for art authentication. In: Proceedings of the National Academy of Sciences (2004) Google Scholar
  110. 110.
    Spafford, E.H., Weeber, S.A.: Software forensics: can we track code to its authors? In: 15th National Computer Security Conference (1992) Google Scholar
  111. 111.
    Jain, A., Griess, F., Connell, S.: On-line signature verification. Pattern Recognit. 35, 2963–2972 (2002) MATHGoogle Scholar
  112. 112.
    Nalwa, V.S.: Automatic on-line signature verification. Proc. IEEE 85, 215–239 (1997) Google Scholar
  113. 113.
    Herbst, B., Coetzer, H.: On an offline signature verification system. In: Proceedings of the 9th Annual South African Workshop on Pattern Recognition (1998) Google Scholar
  114. 114.
    Lei, H., Palla, S., Govindaraju, V.: ER2: an intuitive similarity measure for on-line signature verification. In: IWFHR ’04: Proceedings of the Ninth International Workshop on Frontiers in Handwriting Recognition (IWFHR’04). IEEE Comput. Soc., Los Alamitos (2004) Google Scholar
  115. 115.
    Riha, Z., Matyas, V.: Biometric authentication systems. In: FI MU Report Series (2000) Google Scholar
  116. 116.
    Muralidharan, N., Wunnava, S.: Signature verification: a popular biometric technology. In: Second LACCEI International Latin American and Caribbean Conference for Engineering and Technology (LACCEI’2004), Miami, Florida, USA (2004) Google Scholar
  117. 117.
    Plamondon, R., Lorette, G.: Automatic signature verification and writer identification: the state of the art. Pattern Recognit. 22(2), 107–131 (1989) Google Scholar
  118. 118.
    Ballard, L., Monrose, F., Lopresti, D.P.: Biometric authentication revisited: understanding the impact of wolves in sheep’s clothing. In: Fifteenth USENIX Security Symposium, Vancouver, BC, Canada (2006) Google Scholar
  119. 119.
    Ramann, F., Vielhauer, C., Steinmetz, R.: Biometric applications based on handwriting. In: IEEE International Conference on Multimedia and Expo (ICME ’02) (2002) Google Scholar
  120. 120.
    Ballard, L., Lopresti, D., Monrose, F.: Evaluating the security of handwriting biometrics. In: The 10th International Workshop on Frontiers in Handwriting Recognition (IWFHR06), La Baule, France (2006) Google Scholar
  121. 121.
    Zhu, Y., Tan, T., Wang, Y.: Biometric personal identification based on handwriting. In: 15th International Conference on Pattern Recognition (ICPR’00) (2000) Google Scholar
  122. 122.
    Hamdy, O., Traoré, I.: Cognitive-based biometrics system for static user authentication. In: Fourth International Conference on Internet Monitoring and Protection, Venice/Mestre, Italy, May 24–28, pp. 90–97 (2009) Google Scholar
  123. 123.
    Hamdy, O., Traoré, I.: New physiological biometrics based on human cognitive factors. In: International Conference on Complex, Intelligent and Software Intensive Systems, Fukuoka, Japan, March 16–19, pp. 910–917 (2009) Google Scholar
  124. 124.
    Jain, A.K., Dass, S.C., Nandakumar, K.: Can soft biometric traits assist user recognition. In: SPIE Defense and Security Symposium, Orlando, FL (2004) Google Scholar
  125. 125.
    Jain, A.K., Dass, S.C., Nandakumar, K.: Soft biometric traits for personal recognition systems. In: International Conference on Biometric Authentication (ICBA), Hong Kong (2004) Google Scholar
  126. 126.
    Jacob, B.A., Levitt, S.D.: To catch a cheat. In: Education Next. Available at: (2004) Google Scholar
  127. 127.
    Henderson, N.Y., et al.: Polymer thick-film sensors: possibilities for smartcard biometrics. In: Proceedings of Sensors and Their Applications XI (2001) Google Scholar
  128. 128.
    Henderson, N.J., et al.: Sensing pressure for authentication. In: 3rd IEEE Benelux Signal Processing Symp. (SPS), Leuven, Belgium (2002) Google Scholar
  129. 129.
    Halteren, H.V.: Linguistic profiling for author recognition and verification. In: Proceedings of ACL-2004 (2004) Google Scholar
  130. 130.
    Stamatatos, E., Fakotakis, N., Kokkinakis, G.: Automatic authorship attribution. In: Ninth Conf. European Chap. Assoc. Computational Linguistics, Bergen, Norway (1999) Google Scholar
  131. 131.
    Juola, P., Sofko, J.: Proving and improving authorship attribution. In: Proceedings of CaSTA-04. The Face of Text (2004) Google Scholar
  132. 132.
    Koppel, M., Schler, J.: Authorship verification as a one-class classification problem. In: 21st International Conference on Machine Learning, Banff, Canada (2004) Google Scholar
  133. 133.
    Koppel, M., Schler, J., Mughaz, D.: Text categorization for authorship verification. In: Eighth International Symposium on Artificial Intelligence and Mathematics, Fort Lauderdale, Florida (2004) Google Scholar
  134. 134.
    Ciota, Z.: Speaker verification for multimedia application. In: IEEE International Conference on Systems, Man and Cybernetics (2004) Google Scholar
  135. 135.
    Sanderson, C., Paliwal, K.K.: Information fusion for robust speaker verification. In: Proc. 7th European Conference on Speech Communication and Technology (EUROSPEECH’01), Aalborg (2001) Google Scholar
  136. 136.
    Campbell, J.P.: Speaker recognition: a tutorial. Proc. IEEE 85(9), 1437–1462 (1997) Google Scholar
  137. 137.
    Ratha, N.K., Senior, A., Bolle, R.M.: Automated biometrics. In: International Conference on Advances in Pattern Recognition, Rio de Janeiro, Brazil (2001) Google Scholar
  138. 138.
    Deshpande, S., Chikkerur, S., Govindaraju, V.: Accent classification in speech. In: Fourth IEEE Workshop on Automatic Identification Advanced Technologies (2005) Google Scholar
  139. 139.
    Lin, X., Simske, S.: Phoneme-less hierarchical accent classification. In: Thirty-Eighth Asilomar Conference on Signals, Systems and Computers (2004) Google Scholar
  140. 140.
    Tsai, W.-H., Wang, H.-M.: Automatic singer recognition of popular music recordings via estimation and modeling of solo vocal signals. IEEE Trans. Audio Speech Lang. Process. 14(1), 330–341 (2006) Google Scholar
  141. 141.
    Revett, K.: Behavioral Biometrics: A Remote Access Approach. Wiley, Chichester (2008) Google Scholar
  142. 142.
    Marcel, S., Millan, J.: Person authentication using brainwaves (EEG) and maximum a posteriori model adaptation. IEEE Trans. Pattern Anal. Mach. Intell. 29(4), 743–752 (2007) Google Scholar
  143. 143.
    Thorpe, J., Oorschot, P.C.V., Somayaji, A.: Pass-thoughts: authenticating with our minds. In: Workshop on New Security Paradigms, Lake Arrowhead, California (2011) Google Scholar
  144. 144.
    Lawson, W.: The new wave (“Biometric access & neural control”) (2002). November 24, 2008. Available from:
  145. 145.
    Mohammadi, G., et al.: Person identification by using AR model for EEG signals. In: World Academy of Science, Engineering and Technology (2006) Google Scholar
  146. 146.
    Gahi, Y., et al.: In: New Technologies, Mobility and Security (NTMS’08), Tangier, Virginia, November 5–7, pp. 1–5 (2008) Google Scholar
  147. 147.
    Shye, A., et al.: Power to the people: leveraging human physiological traits to control microprocessor frequency. In: 41st IEEE/ACM International Symposium on Microarchitecture, Como, Italy, November 8–12 (2008) Google Scholar
  148. 148.
    Korotkaya, Z.: Biometrics person authentication: odor (2003). October 12, 2008. Available from:
  149. 149.
    Beritelli, F., Serrano, S.: Biometric identification based on frequency analysis of cardiac sounds. IEEE Trans. Inf. Forensics Secur. 2(3), 596–604 (2007) Google Scholar
  150. 150.
    Phua, K., et al.: Human identification using heart sound. In: Second International Workshop on Multimodal User Authentication, Toulouse, France (2006) Google Scholar
  151. 151.
    Preez, J., Soms, S.H.: Person identification and authentication by using “the way the heart beats”. In: ISSA 2005 New Knowledge Today Conference, Sandton, South Africa (2005) Google Scholar
  152. 152.
    Scotti, S., et al.: Quantitative evaluation of distant student psychophysical responses during the e-learning processes. In: 27th IEEE Annual Conference on Engineering in Medicine and Biology, Shanghai, China, September 1–4 (2005) Google Scholar
  153. 153.
    Yampolskiy, R.V.: Action based user authentication. Int. J. Electron. Secur. Digit. Forensics 1(3), 281–300 (2008) Google Scholar
  154. 154.
    Bekkering, E., Warkentin, M., Davis, K.: A longitudinal comparison of four password procedures. In: Proceedings of the Hawaii International Conference on Business, Honolulu, HI, June (2003) Google Scholar
  155. 155.
    Podd, J., Bunnell, J., Henderson, R.: Cost-effective computer security: cognitive and associative passwords. In: Sixth Australian Conference on Computer-Human Interaction, Hamilton, New Zealand, November 24–27, pp. 304–305 (1996) Google Scholar
  156. 156.
    Brostoff, A.: Improving password system effectivness. PhD Dissertation, Department of Computer Science University College London, September 30, 2004 Google Scholar
  157. 157.
    Brostoff, A.: The science behind passfaces. In: Real User Corporation, June 2004. Available at: Google Scholar
  158. 158.
    Dhamija, R., Perrig, A.: Deja vu: a user study. Using images for authentication. In: Proceedings of the 9th USENIX Security Symposium, Denver, Colorado, August (2000) Google Scholar
  159. 159.
    Angeli, A.D., et al.: Usability and user authentication: Pictorial passwords vs. PIN. In: Contemporary Ergonomics, pp. 253–258. Taylor & Francis, London (2003) Google Scholar
  160. 160.
    Jansen, W., et al.: Picture password: a visual login technique for mobile devices. Retrieved October 24, 2005. Available at:
  161. 161.
    Pointsec. PicturePINs. November, 2002. Available at:
  162. 162.
    Gibson, M., et al.: Musipass: authenticating me softly with my song. In: New Security Paradigms Workshop (NSPW’09), Oxford, UK, September 8–11 (2009) Google Scholar
  163. 163.
    Wiedenbeck, S., et al.: Authentication using graphical passwords: basic results. Retrieved October 23, 2005. Available at:
  164. 164.
    Wiedenbeck, S., et al.: PassPoints: design and longitudinal evaluation of a graphical password system. Int. J. Human-Comput. Stud. 63(1–2) (2005) Google Scholar
  165. 165.
    Blonder, G.E.: Graphical passwords. United States Patent 5559961 (1996) Google Scholar
  166. 166.
    Varenhorst, C.: Passdoodles; a lightweight authentication method. July 27, 2004. Available at:
  167. 167.
    Jermyn, I., et al.: The design and analysis of graphical passwords. In: Proceedings of the 8th USENIX Security Symposium, Washington, D.C., August 23–36 (1999) Google Scholar
  168. 168.
    Thorpe, J., v. Oorschot, P.: Towards secure design choices for implementing graphical passwords. In: 20th Annual Computer Security Applications Conference, Tucson, Arizona, December 6–10 (2004) Google Scholar
  169. 169.
    Ross, S.: Is it just my imagination? Retrieved November 4, 2005. Available at:
  170. 170.
    Renaud, K., McBryan, T.: How viable are Stubblefield and Simon’s inkblots as password cues? In: PUMP 2010, University of Abertay, Dundee, 6 September (2010) Google Scholar
  171. 171.
    Renaud, K., McBryan, T., Siebert, P.: Password cueing with cue(ink)blots. In: IADIS Computer Graphics and Visualization 2008 (CGV 2008), Amsterdam, The Netherlands (2008) Google Scholar
  172. 172.
    Stubblefield, A., Simon, D.: Inkblot authentication. Microsoft TechReport# MSR-TR-2004-85 (August 2004). Available at:
  173. 173.
    Porter, S.: Stronger passwords through visual authentication: handwing. University of Glasgow. Retrieved November 4, 2005. Available at:
  174. 174.
    Standring, S.: Gray’s Anatomy: The Anatomical Basis of Medicine and Surgery. Churchill Livingstone, Oxford (2004) Google Scholar
  175. 175.
    Erdogan, H., et al.: Multi-modal person recognition for vehicular applications. Lect. Notes Comput. Sci. 3541, 366–375 (2005) Google Scholar
  176. 176.
    Marin, J., Ragsdale, D., Surdu, J.: A hybrid approach to the profile creation and intrusion detection. In: DARPA Information Survivability Conference and Exposition (DISCEX II’01) (2001) Google Scholar
  177. 177.
    Bergadano, F., Gunetti, D., Picardi, C.: User authentication through keystroke dynamics. ACM Trans. Inf. Syst. Secur. 5(4), 367–397 (2002) Google Scholar
  178. 178.
    Frantzeskou, G., Gritzalis, S., MacDonell, S.: Source code authorship analysis for supporting the cybercrime investigation process. In: 1st International Conference on eBusiness and Telecommunication Networks—Security and Reliability in Information Systems and Networks Track, Setubal, Portugal. Kluwer Academic, Dordrecht (2004) Google Scholar
  179. 179.
    Colombi, J., et al.: Cohort selection and word grammer effects for speaker recognition. In: IEEE International Conference on Acoustics, Speech, and Signal Processing, Atlanta, GA (1996) Google Scholar
  180. 180.
    Tsai, W.-H., Wang, H.-M.: Automatic singer recognition of popular music recordings via estimation and modeling of solo vocal signals. In: IEEE Transactions on Audio, Speech and Language Processing, January 2006 Google Scholar
  181. 181.
    Crompton, M.: Biometrics and privacy: the end of the world as we know it or the white knight of privacy? In: 1st Biometrics Institute Conference (2003) Google Scholar
  182. 182.
    Prassas, G., Pramataris, K.C., Papaemmanouil, O.: Dynamic recommendations in internet retailing. In: 9th European Conference on Information Systems (ECIS 2001) (2001) Google Scholar
  183. 183.
    Liang, T.P., Lai, H.-J.: Discovering user interests from web browsing behavior. In: Proceedings of the Hawaii International Conference on Systems Sciences, Hawaii, USA (2002) Google Scholar
  184. 184.
    Fu, Y., Shih, M.: A framework for personal web usage mining. In: International Conference on Internet Computing (IC’2002), Las Vegas, NV (2002) Google Scholar
  185. 185.
    Goecks, J., Shavlik, J.: Learning users’ interests by unobtrusively observing their normal behavior. In: Proceedings of the International Conference on Intelligent User Interfaces, New Orleans, LA (2000) Google Scholar
  186. 186. TV that watches you: the prying eyes of interactive television. A report by the center for digital democracy, June 2001. Available from:
  187. 187.
    Jain, K., Nandakumar, K., Ross, A.: Score normalization in multimodal biometric systems. In: Pattern Recognition (2005) Google Scholar
  188. 188.
    Dahel, S.K., Xiao, Q.: Accuracy performance analysis of multimodal biometrics. In: IEEE Information Assurance Workshop on Systems, Man and Cybernetics Society (2003) Google Scholar
  189. 189.
    Humm, A., Hennebert, J., Ingold, R.: Scenario and survey of combined handwriting and speech modalities for user authentication. In: 6th International Conference on Recent Advances in Soft Computing (RASC’06), Canterbury, UK (2006) Google Scholar

Copyright information

© Springer-Verlag London Limited 2011

Authors and Affiliations

  1. 1.University of LouisvilleLouisvilleUSA

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