Abstract
People often prefer to preserve a lot of confidential information in different electronic devices such as laptops, desktops, tablets, etc. Access to these personalized devices are managed through well known and robust user authentication techniques. Therefore, designing authentication methodologies using various input modalities received much attention of the researchers of this domain. Since we access such personalized devices everywhere including crowded places such as offices, public places, meeting halls, etc., the risk of an imposter gaining one’s identification information becomes highly feasible. One of the oldest but effective form of identity theft by observation is known as shoulder surfing. Patterns drawn by the authentic user on tablet surfaces or keys typed through keyboard can easily be recognized through shoulder surfing. Contact-less user interface devices such as Leap Motion controller can be used to mitigate some of the limitations of existing contact-based input methodologies. In this paper, we propose a robust user authentication technique that has been designed to counter the chances of getting one’s identity stolen by shoulder surfing. Our results reveal that, the proposed methodology can be quite effective to design robust user authentication systems, especially for personalized electronic devices.
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Jansen, W.: Authenticating users on handheld devices. In: Proceedings of the Canadian Information Technology Security Symposium, pp. 1–12 (2003)
Iwai, Y., Shimizu, H., Yachida, M.: Real-time context-based gesture recognition using HMM and automaton. In: International Workshop on Recognition, Analysis, and Tracking of Faces and Gestures in Real-Time Systems, pp. 127–134 (1999)
Rashid, O., Al-Hamadi, A., Michaelis, B.: A framework for the integration of gesture and posture recognition using HMM and SVM. In: IEEE International Conference on Intelligent Computing and Intelligent Systems, vol. 4, pp. 572–577 (2009)
Shrivastava, R.: A hidden Markov model based dynamic hand gesture recognition system using OpenCV. In: 3rd IEEE International Conference on Advance Computing, pp. 947–950 (2013)
Rabiner, L.: A tutorial on hidden Markov models and selected applications in speech recognition. In: Proceedings of the IEEE, vol. 77, no. 2, pp. 257–286 (1989)
Yamato, J., Ohya, J., Ishii, K.: Recognizing human action in time-sequential images using hidden Markov model. In: IEEE Computer Society Conference on Computer Vision and Pattern Recognition, pp. 379–385 (1992)
Seo, H., Kang Kim, H.: User Input Pattern-Based Authentication Method to Prevent Mobile E-Financial Incidents. In: Ninth IEEE International Symposium on Parallel and Distributed Processing with Applications Workshops (ISPAW), pp. 382–387 (2011)
Sheng, Y., Phoha, V. V., Rovnyak, S. M.: A parallel decision tree-based method for user authentication based on keystroke patterns. In: IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics, vol. 35, no. 4, pp. 826–833 (2005)
Mengyu, Q., Suiyuan, Z., Sung, A. H., Qingzhong, L.: A Novel Touchscreen-Based Authentication Scheme Using Static and Dynamic Hand Biometrics. In: 39th Annual IEEE conference on Computer Software and Applications, vol. 2, pp. 494–503 (2015)
Syed, Z., Banerjee, S., Qi, C., Cukic, B.: Effects of User Habituation in Keystroke Dynamics on Password Security Policy. In: IEEE 13th International Symposium on High-Assurance Systems Engineering (HASE), pp. 352–359 (2011)
Frank, M., Biedert, R., Ma, E., Martinovic, I.; Song, D.: Touchalytics: On the Applicability of Touchscreen Input as a Behavioral Biometric for Continuous Authentication. In: IEEE Transactions on Information Forensics and Security, vol. 8, no. 1, pp. 136–148 (2013)
Vamsikrishna, K., Dogra, D. P., Desarkar, M. S.: Computer Vision Assisted Palm Rehabilitation With Supervised Learning. In: IEEE Transactions on Biomedical Engineering, DOI:10.1109/TBME.2015.2480881 (2015)
Rahman, M., Ahmed, M., Qamar, A., Hossain, D., Basalamah, S.: Modeling therapy rehabilitation sessions using non-invasive serious games. In: Proceedings of the IEEE International Symposium on Medical Measurements and Applications, pp. 1–4 (2014)
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Bhoi, S., Dogra, D.P., Roy, P.P. (2017). On-line Gesture Based User Authentication System Robust to Shoulder Surfing. In: Raman, B., Kumar, S., Roy, P., Sen, D. (eds) Proceedings of International Conference on Computer Vision and Image Processing. Advances in Intelligent Systems and Computing, vol 460. Springer, Singapore. https://doi.org/10.1007/978-981-10-2107-7_50
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DOI: https://doi.org/10.1007/978-981-10-2107-7_50
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