Unlock A Device with Pressure and Rhythm Based Password

Unlock A Device with Pressure and Rhythm Based Password

When people open their doors, they usually use the keys they carry in their pockets. As an alternative to these used keys, it is possible to open the doors which are authorized with RFID-enabled key holders or ID cards. But it seems that different alternatives have not been developed much. Moreover, none of them carries the sensory understanding dimension of the person and it is not possible to determine whether or not the entrance request has been made by that person. In this study, both the identification of the person and the opening of the door are ensured by considering both the stroking rhythm and the stroke force of a buttoner placed in the door. Thus, it is possible to open the door according to the person's identity and authority without carrying any object beside it, and it will have a unique original value. The milliseconds between each stroke for the stroke of the quill are recorded in the generated database. Comparison is made with the data obtained in the next stroke and the person is used for verification. In addition, the pressure data of the person is also kept in the database for each stroke and compared. In the study, the data of two different people were recorded in the system and the information of the people using the subjective button was recorded. Then, in addition to these two different people, a total of 15 people, including 13 different people, were allowed to use the system. In total, 50 door opening requests data were recorded and 87.5% success rate was obtained.

___

  • G.J. Anderson. U.S. Patent No. 6,509,847. Washington, DC: U.S. Patent and Trademark Office. 2003.
  • Y. Zhong, Y. Deng, A.K. Jain. “Keystroke dynamics for user authentication”, 2012 IEEE Computer Society Conference on Computer
  • Vision and Pattern Recognition Workshops (CVPRW 2012). Rhode Island, USA, 2012.
  • M.S. Obaidat, B. Sadoun. “Keystroke dynamics-based authentication. Biometrics”. US: Springer, 1996, pp 213–229.
  • R. Giot, M. El-Abed, C. Rosenberger. “Keystroke dynamics with low constraints svm based passphrase enrollment”. In Biometrics: Theory, Applications, and Systems, 2009. BTAS'09. IEEE 3rd International Conference on IEEE. 2009.
  • S.S. Bender, H.J. Postley. U.S. Patent No. 7,206,938. Washington, DC: U.S. Patent and Trademark Office. 2007.
  • P.S. Teh, A.B.J. Teoh, C. Tee, T.S. Ong. “Keystroke dynamics in password authentication enhancement”. Expert Systems with Applications, vol. 37. 12, 2010, pp 8618-8627.
  • T.Y. Chang, C.J. Tsai, Y.J. Yang, P.C. Cheng. “User authentication using rhythm click characteristics for non-keyboard devices”. In Proceedings of the 2011 International Conference on Asia Agriculture and Animal IPCBEE, Singapoore, 2011.
  • T.Y. Chang, Y.J. Yang, C.C. Peng. “A personalized rhythm click-based authentication system”. Information Management & Computer Security, vol. 18. 2, 2010, pp 72-85.
  • D.L. Ashbrook, F.X. Lin, S.M. Whtie. U.S. Patent Application No. 13/092,383, 2012.
  • Y.V. Fedorova, T.R. Ruddy, M.S. Nunuparov. U.S. Patent No. 7,536,556. Washington, DC: U.S. Patent and Trademark Office, 2009.
  • G.R. Hird. U.S. Patent Application No. 13/484,836, 2013.
  • J.O. Wobbrock. “Tapsongs: tapping rhythm-based passwords on a single binary sensor”. In Proceedings of the 22nd annual ACM symposium on User interface software and technology. New York, USA, 2009.
  • Y. Chen, J. Sun, R. Zhang, Y. Zhang. “Your song your way: Rhythm-based two-factor authentication for multi-touch mobile devices”. In Computer Communications (INFOCOM), 2015 IEEE Conference on. Kowloon, Hong Kong, 2015.
  • J.D. Lee, Y.S. Jeong, J.H. Park. “A rhythm-based authentication scheme for smart media devices”. The Scientific World Journal, vol. 2014, 2014.
  • S.S. Hwang, S. Cho, S. Park. “Keystroke dynamics-based authentication for mobile devices”. Computers & Security. vol. 28. 1-2, 2009, pp 85-93.
  • T. Tuncer, and Y. Sönmez. "Block based data hiding method for images." European Journal of Technique 7.2 (2017): 85-95.
  • F. Cherifi, B. Hemery, R. Giot, M. Pasquet, C. Rosenberger. “Performance evaluation of behavioral biometric systems”. In Behavioral Biometrics for Human Identification: Intelligent Applications, 2010, pp 57-74.