Smart Lock 인증 기법에 대한 연구동향 분석

  • 조금환 (성균관대학교 전자전기컴퓨터공학과) ;
  • 이승진 (성균관대학교 전자전기컴퓨터공학과) ;
  • 김형식 (성균관대학교 전자전기컴퓨터공학과)
  • 발행 : 2018.02.28

초록

전통적인 인증 기법(예: 패스워드, PINs, 안드로이드 패턴 락)들은 사용빈도가 많은 모바일 기기의 특성으로 인해 사용자에게 불편함을 가중시킨다. 본 논문에서는 사용성을 고려한 Smart Lock 인증 기법에서 사용되는 요소 기술에 대한 연구 동향에 대해 분석하였다. 요소 기술 한 가지를 독립적으로 사용하는 방법보다는 다양한 요소 기술들을 동시에 활용한다면 보안성과 사용성을 모두 만족할 수 있는 인증 기법으로 사용될 것이다.

키워드

참고문헌

  1. Apple Touch ID, https://support.apple.com/en-us/HT204587, Accessed: 2018-02-01.
  2. Iris Scanner, http://www.samsung.com/global/galaxy/galaxy-s8/security/ Accessed: 2018-02-01.
  3. Ivan Cherapau, Ildar Muslukhov, Nalin Asanka, Konstantin Beznosov, "On the Impact of Touch ID on iPhone Passcodes," Usenix Symposium On Usable Privacy and Security, 2015.
  4. Samsung Smart Lock, https://www.samsung.com/us/support/answer/ANS00062631/, Accessed: 2018-02-01.
  5. Hugo Gascon, Sebastian Uellenbeck, Christopher Wolf, and Konrad Rieck, "Continuous authentication on mobile devices by analysis of typing motion behavior," In Proceedings of GI Conference Sicherheit, 2014.
  6. Yazan Badin, "Contextual authentication using mobile phone movements to authenticate owners implicitly," Master Thesis, University of Twente Department of Computer Science, Enschede, 2016.
  7. Javid Maghsoudi, and Charles C. Tappert, "A behavioral biometrics user authentication study using motion data from android smartphones," European Intelligence and Security Informatics Conference, IEEE, 2016.
  8. Wei-Han Lee, and Ruby Lee, "Implicit sensor-based authentication of smartphone users with smartwatch," In Proceedings of the Hardware and Architectural Support for Security and Privacy, 2016.
  9. Wei-Han Lee, and Ruby B. Lee, "Multi-sensor authentication to improve smartphone security," In Proceedings of International Conference on Information Systems Security and Privacy, 2017.
  10. Hilmi G. Kayacik, Mike Just, Lynne Baillie, and David Aspinall, "Data driven authentication: On the effectiveness of user behaviour modelling with mobile device sensors," Mobile Security Technologies, 2014.
  11. Lex Fridman, Steven Weber, Rachel Greenstadt, and Moshe Kam, "Active authentication on mobile devices via stylometry, application usage, web browsing, and GPS Location," System Journal, IEEE, 2017.
  12. Senaka Buthpitiya, Ying Zhang, Anind K. Dey, and Martin Griss, "n-gram geo-trace modeling", International Conference on Pervasive Computing, 2011.
  13. Elain Shi, Yuan Niu, Markus Jakobsson, and Richard Chow, "Implicit authentication through learning user behavior," In Proceedings of International Conference on Information Security, 2010.
  14. Z. Chair and P. Varshney, "Optimal data fusion in multiple sensor detection system", IEEE Transactions on Aerospace and Electronic System, 1986.
  15. Ioannis Agadakos, Per Hallgren, Dimitrios Damopoulos, Andrei Sabelfeld, and Georgios Portokalidis, "Location-enhanced Authentication using the IoT Because You Cannot Be in Two Places at Once," In Proceedings of Annual Computer Security Applications Conference, 2016.
  16. John Paul Dunning, "Taming the Blue Beast A Survey of Bluetooth-Based Threats," IEEE Security & Privacy 8 (2), 2010.
  17. Mossab Baloul, Estelle Cherrier, and Christophe Rosenberger, " Challenge based speaker recognition for mobile authentication," In Proceedings of the International Conference on Biometrics Special Interest Group, IEEE, 2012.
  18. Cory Cornelius, Zachary Marois, Jacob Sorber, Ron Peterson, Shrirang Mare, and David Kotz, "Vocal resonance as a passive biometric," 2014.
  19. Amitava Das, Ohil K Manyam, Makarand Tapaswi, and Veeresh Taranalli, "Multilingual spoken-password based user authentication in emerging economiesusing cellular phone networks," In Spoken Language Technology Workshop, IEEE, 2008.
  20. Max Kunz, Klaus Kasper, Herbert Reininger, Manuel Möbius, and Jonathan Ohms, "Continuous Speaker Verication in Realtime," In Proceedings of the International Conference on Biometrics Special Interest Group, IEEE, 2011.
  21. Mumtaj Begam Lindasalwa Muda and I. Elamvazuthi, "Voice Recognition Algorithms using Mel Frequency Cepstral Coecient (MFCC) and Dynamic Time Warping (DTW) Techniques," Journal Of Computing 2, 3, 138-143, 2010.
  22. X. D. Huang, Y. Ariki, and M. A. Jack, "Hidden Markov Models for Speech Recognition," 1990.
  23. Florentin Thullier, Bruno Bouchard and Bob-Antoine J. Menelas, "A Text-Independent Speaker Authentication System for Mobile Devices," cryptography, 1(3), 16, 2017. https://doi.org/10.3390/cryptography1030016
  24. Andrew Boles and Paul Rad, "Voice Biometrics: Deep Learning-based Voiceprint Authentication," In Proceeding of International Conference on System of Systems Engineering, 2017.
  25. Laurynas Dovydaitis, Tomas Rasymas, and Vytautas Rudzionis, "Speaker Authentication System Based on Voice Biometrics and Speech Recognition," In Proceedings of International Conference on Business Information Systems, 2017.
  26. Zheng Yan and Sihui Zhao, "A Usable Authentication System based on Personal Voice Challenge," In Proceedings of International Conference on Advanced Cloud and Big Data, 2016.
  27. R.C. Johnson, Terrance E. Boult, and Walter J. Scheirer, "Voice authentication using short phrases: Examining accuracy, security and privacy issues," In Proceedings of IEEE 6th International Conference on Biometric: Theory, Applications and Systems, 2017.