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http://dx.doi.org/10.3837/tiis.2019.06.016

User Identification Using Real Environmental Human Computer Interaction Behavior  

Wu, Tong (School of Cyberspace Security, Beijing University of Posts and Telecommunications)
Zheng, Kangfeng (School of Cyberspace Security, Beijing University of Posts and Telecommunications)
Wu, Chunhua (School of Cyberspace Security, Beijing University of Posts and Telecommunications)
Wang, Xiujuan (School of Computer, Beijing University of Technology)
Publication Information
KSII Transactions on Internet and Information Systems (TIIS) / v.13, no.6, 2019 , pp. 3055-3073 More about this Journal
Abstract
In this paper, a new user identification method is presented using real environmental human-computer-interaction (HCI) behavior data to improve method usability. User behavior data in this paper are collected continuously without setting experimental scenes such as text length, action number, etc. To illustrate the characteristics of real environmental HCI data, probability density distribution and performance of keyboard and mouse data are analyzed through the random sampling method and Support Vector Machine(SVM) algorithm. Based on the analysis of HCI behavior data in a real environment, the Multiple Kernel Learning (MKL) method is first used for user HCI behavior identification due to the heterogeneity of keyboard and mouse data. All possible kernel methods are compared to determine the MKL algorithm's parameters to ensure the robustness of the algorithm. Data analysis results show that keyboard data have a narrower range of probability density distribution than mouse data. Keyboard data have better performance with a 1-min time window, while that of mouse data is achieved with a 10-min time window. Finally, experiments using the MKL algorithm with three global polynomial kernels and ten local Gaussian kernels achieve a user identification accuracy of 83.03% in a real environmental HCI dataset, which demonstrates that the proposed method achieves an encouraging performance.
Keywords
User Identification; Biometric; Multiple Kernel Learning (MKL); Keystroke Dynamic; Mouse Dynamic;
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1 Chao Shen, Zhongmin Cai, Xiaohong Guan and Jinpei Cai, "A hypo-optimum feature selection strategy for mouse dynamics in continuous identity authentication and monitoring," in Proc. of 2010 IEEE International Conference on Information Theory and Information Security, pp. 349-353, December 17-19, 2010.
2 Soumik Mondal and Patrick Bours, "Combining keystroke and mouse dynamics for continuous user authentication and identification," in Proc. of 2016 IEEE International Conference on Identity, Security and Behavior Analysis (ISBA), February 29-March 2, 2016.
3 A.A.E. Ahmed and I. Traore, "Anomaly intrusion detection based on biometrics," in Proc. of the Sixth Annual IEEE Systems, Man and Cybernetics (SMC) Information Assurance Workshop, June 15-17, 2005.
4 Issa Traore, Isaac Woungang, Mohammad S. Obaidat, Youssef Nakkabi and Iris Lai, "Combining mouse and keystroke dynamics biometrics for risk-based authentication in web environments," in Proc. of 2012 Fourth International Conference on Digital Home, November 23-25, 2012.
5 Jain Shing Wu, Chih Ta Lin, Yuh Jye Lee and Song Kong Chong, "Keystroke and mouse movement profiling for data loss prevention," Journal of Information Science & Engineering, vol. 31, no.1, pp. 23-42, January 2015.
6 Harini Jagadeesan and Michael S. Hsiao, "A novel approach to design of user re-authentication systems," in Proc. of 2009 IEEE 3rd International Conference on Biometrics: Theory, Applications, and Systems, September 28-30, 2009.
7 Maja Pusara, "An Examination of User Behavior for Re-authentication," PhD thesis, Center for Education and Research in Information Assurance and Security, Purdue University, August, 2007.
8 Hong-Qiao WANG, Fu-Chun SUN, Yan-Ning CAI, Ning CHEN and Lin-Ge DING, "On multiple kernel learning methods," Acta Automatica Sinica, vol. 36, no. 8, pp. 1037-1050, September, 2010.   DOI
9 Fridman, L., Stolerman, A., Acharya, S., Brennan, P., Juola, P., Greenstadt, R., and Kam, M., "Multi-modal decision fusion for continuous authentication," Computers & Electrical Engineering, vol. 41, pp. 142-156, January, 2015.   DOI
10 Pin Shen Teh, Andrew Beng Jin Teoh, and Shigang Yue, "A survey of keystroke dynamics biometrics," The Scientific World Journal, vol. 2013, pp. 1-24, 2013.
11 John Leggett, Glen Williams, Mark Usnick, and Mike Longnecker, "Dynamic identity verification via keystroke characteristics," International Journal of Man-Machine Studies, vol. 35, no. 6, pp. 859-870, December, 1991.   DOI
12 Gaines, R. Stockton, William Lisowski, S. James Press, and Norman Shapiro, "Authentication by Keystroke Timing: Some Preliminary Results," RAND Corporation, 1980.
13 Gamboa Hugo and Ana LN Fred, "An Identity Authentication System Based On Human Computer Interaction Behaviour," in Proc. of International Workshop on Pattern Recognition in Information Systems, vol. 2003, pp. 46-55, April, 2003.
14 Salil Partha Banerjee and Damon Woodard, "Biometric Authentication and Identification Using Keystroke Dynamics: A Survey," Journal of Pattern Recognition Research, vol. 7, no. 1, pp. 116-139, July, 2012.   DOI
15 Md Liakat Ali, John V. Monaco, Charles C. Tappert, and Meikang Qiu, "Keystroke Biometric Systems for User Authentication," Journal of Signal Processing Systems, vol. 86, no. 2-3, pp. 175-190, March, 2016.
16 Daniele Gunetti and Claudia Picardi, "Keystroke analysis of free text," ACM Transactions on Information and System Security, vol. 8, no. 3, pp. 312-347, August, 2005.   DOI
17 Soumik Mondal and Patrick Bours, "A computational approach to the continuous authentication biometric system," Information Sciences, vol. 304, pp. 28-53, May, 2015.   DOI
18 Clint Feher, Yuval Elovici, Robert Moskovitch, Lior Rokach and Alon Schclar, "User identity verification via mouse dynamics," Information Sciences, vol. 201, pp. 19-36, October, 2012.   DOI
19 Nan Zheng, Aaron Paloski and Haining Wang, "An efficient user verification system via mouse movements," in Proc. of the 18th ACM conference on Computer and communications security, pp. 139-150, October 17-21, 2011.
20 Soumik Mondal and Patrick Bours, "Continuous authentication using mouse dynamics," in Proc. of 2013 International Conference of the BIOSIG Special Interest Group (BIOSIG), September 5-6, 2013.
21 C. Shen, Z. Cai, X. Guan, H. Sha and J. Du, "Feature Analysis of Mouse Dynamics in Identity Authentication and Monitoring," in Proc. of 2009 IEEE International Conference on Communications, pp. 1-5, June 14-18, 2009.
22 Bailey, Kyle O., James S. Okolica, and Gilbert L. Peterson, "User identification and authentication using multi-modal behavioral biometrics," Computers & Security, vol. 43, pp. 77-89, June, 2014.   DOI
23 Pin Shen Teh, Shigang Yue and Andrew B.J. Teoh, "Improving keystroke dynamics authentication system via multiple feature fusion scheme," in Proc. of 2012 International Conference on Cyber Security, Cyber Warfare and Digital Forensic (CyberSec), pp. 277-282, June 26-28, 2012.
24 Aythami Morales, Elena Luna-Garcia, Julian Fierrez and Javier Ortega-Garcia, "Score normalization for keystroke dynamics biometrics," in Proc. of 2015 International Carnahan Conference on Security Technology (ICCST), pp. 223-228, September 21-24, 2015.
25 Gert R.G. Lanckriet, Nello Cristianini, Peter Bartlett, Laurent El Ghaoui and Michael I. Jordan, "Learning the Kernel Matrix with Semi-Definite Programming," Journal of Machine Learning Research, vol. 5, pp. 27-72, January, 2004.
26 Changsheng Wu, Wenbo Ding, Ruiyuan Liu, et al., "Keystroke dynamics enabled authentication and identification using triboelectric nanogenerator array," Materials Today, vol. 21, no. 3, pp. 216-222, April, 2018.   DOI
27 Ahmed Awad E. Ahmed and Issa Traore, "A new biometric technology based on mouse dynamics," IEEE Transactions on dependable and secure computing, vol. 4, no. 3, pp. 165-179, July, 2007.   DOI
28 Youssef Nakkabi, Issa Traore and Ahmed Awad E. Ahmed, "Improving mouse dynamics biometric performance using variance reduction via extractors with separate features," IEEE Transactions on Systems, Man, and Cybernetics-Part A: Systems and Humans, vol. 40, no. 6, pp. 1345-1353, November, 2010.   DOI
29 Naini, F. M., Unnikrishnan, J., Thiran, P., and Vetterli, M, "Where You Are Is Who You Are: User Identification by Matching Statistics," IEEE Transactions on Information Forensics and Security, vol. 11, no. 2, pp. 358-372, February, 2016.   DOI
30 Michael Fairhurst, Meryem Erbilek, and Marjory Da Costa-Abreu, "Selective review and analysis of aging effects in biometric system implementation," IEEE transactions on human-machine systems, vol. 45, no. 3, pp. 294-303, June, 2015.   DOI
31 Fabian Monrose and Aviel Rubin, "Authentication via keystroke dynamics," in Proc. of the 4th ACM conference on Computer and communications security, pp. 48-56, April 01-04, 1997.
32 Tomer Shimshon, Robert Moskovitch, Lior Rokach and Yuval Elovici, "Continuous Verification Using Keystroke Dynamics," in Proc. of International Conference on Computational Intelligence and Security, pp. 411-415, December, 2010.
33 Paulo Henrique Pisani and Ana Carolina Lorena, "Emphasizing typing signature in keystroke dynamics using immune algorithms," Applied Soft Computing, vol. 34, pp. 178-193, September, 2015.   DOI
34 Fabian Monrosea and Aviel D. Rubin, "Keystroke dynamics as a biometric for authentication," Future Generation Computer Systems, vol. 16, no. 4, pp. 351-359, February, 2000.   DOI
35 M. Villani, C. Tappert, Giang Ngo, J. Simone, H.St. Fort and Sung-Hyuk Cha, "Keystroke Biometric Recognition Studies on Long-Text Input under Ideal and Application-Oriented Conditions," in Proc. of 2006 Conference on Computer Vision and Pattern Recognition Workshop (CVPRW'06), June 17-22, 2006.
36 Arik Messerman, Tarik Mustafic, Seyit Ahmet Camtepe and Sahin Albayrak, "Continuous and non-intrusive identity verification in real-time environments based on free-text keystroke dynamics," in Proc. of 2011 International Joint Conference on Biometrics (IJCB), October 11-13, 2011.
37 P. S. Dowland, S. M. Furnell and M. Papadaki, "Keystroke analysis as a method of advanced user authentication and response," Security in the Information Society, pp. 215-226, 2002.
38 Ahmed A. Ahmed and Issa Traore. "Biometric recognition based on free-text keystroke dynamics," IEEE transactions on cybernetics, vol. 44, no. 4, pp. 458-472, April, 2014.   DOI
39 William Stafford Noble, "Support vector machine applications in computational biology," Kernel methods in computational biology, pp. 71-92, 2004.
40 Igor Kononenko, Edvard Simec and Marko Robnik-Sikonja, "Overcoming the myopia of inductive learning algorithms with RELIEFF," Applied Intelligence, vol. 7, no. 1, pp. 39-55, January 1997.   DOI
41 Alain Rakotomamonjy, Francis R. Bach, Stephane Canu and Yves Grandvalet, "SimpleMKL," Journal of Machine Learning Research, vol. 9, no. 11, pp. 2491-2521, November, 2008.
42 G. R. G. Lanckriet, T. De Bie, N. Cristianini, M. I. Jordan and W. S. Noble, "A statistical framework for genomic data fusion," Bioinformatics, vol. 20, no. 16, pp. 2626-2635, May, 2004.   DOI
43 Jingjing Yang, Yonghong Tian, Ling-Yu Duan, Tiejun Huang and Wen Gao, "Group-sensitive multiple kernel learning for object recognition," IEEE Transactions on Image Processing, vol. 21, no. 5, pp. 2838-2852, May, 2012.   DOI
44 Wan-Jui Lee, Sergey Verzakov and Robert P. W. Duin, "Kernel Combination Versus Classifier Combination," in Proc. of International Workshop on Multiple Classifier Systems, pp. 22-31, May 23-25, 2007.
45 Paul Pavlidis, Jason Weston, Jinsong Cai and William Noble Grundy, "Gene functional classification from heterogeneous data," in Proc. of the fifth annual international conference on Computational biology - RECOMB '01, pp. 249-255, April 22-25, 2001.
46 G. R. G. Lanckriet, M. Deng, N. Cristianini, M. I. Jordan and W. S. Noble, "Kernel-based data fusion and its application to protein function prediction in yeast," Biocomputing, pp. 300-311, December, 2003.
47 Yi-Ren Yeh, Ting-Chu Lin, Yung-Yu Chung and Yu-Chiang Frank Wang, "A Novel Multiple Kernel Learning Framework for Heterogeneous Feature Fusion and Variable Selection," IEEE Transactions on Multimedia, vol. 14, no. 3, pp. 563-574, June, 2012.   DOI
48 Kenji Kira and Larry A. Rendell, "The feature selection problem: Traditional methods and a new algorithm," in Proc. of the tenth national conference on Artificial intelligence, pp. 129-134, July 12-16, 1992.
49 Salah Althloothi, Mohammad H. Mahoor, Xiao Zhang and Richard M. Voyles, "Human activity recognition using multi-features and multiple kernel learning," Pattern Recognition, vol. 47, no. 5, pp. 1800-1812, May, 2014.   DOI
50 Shengye Yan, Xinxing Xu, Dong Xu, Stephen Lin and Xuelong Li, "Image Classification With Densely Sampled Image Windows and Generalized Adaptive Multiple Kernel Learning," IEEE Transactions on Cybernetics, vol. 45, no. 3, pp. 381-390, March, 2015.   DOI