International journal of advanced smart convergence

The Institute of Internet, Broadcasting and Communication (한국인터넷방송통신학회)
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Analyzing Input Patterns of Smartphone Applications in Touch Interfaces

  • Bahn, Hyokyung (Department of Computer Engineering, Ewha University) ;
  • Kim, Jisun (Department of Computer Engineering, Ewha University)
  • Received : 2021.09.24
  • Accepted : 2021.10.04
  • Published : 2021.12.31
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Abstract

Touch sensor interface has become the most useful input device in a smartphone. Unlike keypad/keyboard interfaces used in electronic dictionaries and feature phones, smartphone's touch interfaces allow for the recognition of various gestures that represent distinct features of each application's input. In this paper, we analyze application-specific input patterns that appear in smartphone's touch interfaces. Specifically, we capture touch input patterns from various Android applications, and analyze them. Based on this analysis, we observe a certain unique characteristics of application's touch input patterns. This can be utilized in various useful areas like user authentications, prevention of executing application by illegal users, or digital forensic based on logged touch patterns.

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Acknowledgement

This work was supported in by the ICT R&D program of MSIP/IITP (2020-0-00121, development of data improvement and dataset correction technology based on data quality assessment) and (2019-0-00074, developing system software technologies for emerging new memory that adaptively learn workload characteristics).

References

  1. T. Li, M. Zhang, H. Cao, Y. Li, S. Tarkoma, and P. Hui, "What apps did you use? understanding the long-term evolution of mobile app usage," Proceedings of the World Wide Web Conference, pp 66-76, 2020. DOI: https://doi.org/10.1145/3366423.3380095
  2. D. Kim, S. Lee, and H. Bahn, "An adaptive location detection scheme for energy-efficiency of smartphones," Pervasive and Mobile Computing, vol. 31, pp. 67-78, 2016. DOI: https://doi.org/10.1016/j.pmcj.2016.04.012
  3. E. Lee and H. Bahn, "Electricity usage scheduling in smart building environments using smart devices," The Scientific World Journal, vol. 2013, Article 468097, pp. 1-11, 2013. DOI: https://doi.org/10.1155/2013/468097
  4. T. Kim, H. Bahn, and K. Koh, "Popularity-aware interval caching for multimedia streaming servers," Electronics Letters, vol. 39, no. 21, pp. 1555-1557, 2003. DOI: https://doi.org/10.1049/el:20030965
  5. R. Ikeda, K. Hakka, and B. Shizuki, "Hover-based reachability technique for executing single-touch gesture on smartphone," in Proc. Asian CHI Symposium, pp. 9-15, 2021. DOI: https://doi.org/10.1145/3429360.3468171
  6. A. Acien, A. Morales, and R. Vera-Rodriguez, "Smartphone sensors for modeling human-computer interaction: General outlook and research datasets for user authentication," in Proc. 44th IEEE COMPSAC Conf., 2020. DOI: https://doi.org/10.1109/COMPSAC48688.2020.00-81
  7. A. Suharsono and D. Liang, "Hand stability based features for touch behavior smartphone authentication," in Proc. 3rd IEEE Conf. Knowledge Innovation and Invention, 2020. DOI: https://doi.org/10.1109/ICKII50300.2020.9318982
  8. D. Kim, E. Lee, S. Ahn, H. Bahn, "Improving the storage performance of smartphones through journaling in nonvolatile memory," IEEE Trans. Consumer Electronics, vol. 59, no. 3, pp. 556-561, 2013. DOI: https://doi.org/10.1109/TCE.2013.6626238
  9. J. Park, H. Lee, S. Hyun, K. Koh, H. Bahn, "A cost-aware page replacement algorithm for NAND flash based mobile embedded systems," in Proc. the seventh ACM international conference on Embedded software (EMSOFT), 2009. DOI: https://doi.org/10.1145/1629335.1629377
  10. O. Kwon, H. Bahn, and K. Koh, "Popularity and prefix aware interval caching for multimedia streaming servers," in Proc. 8th IEEE International Conference on Computer and Information Technology, pp. 555-560, 2008. DOI: https://doi.org/10.1109/CIT.2008.4594735
  11. C. Shen, Y. Zhang, X. Guan and R. A. Maxion, "Performance analysis of touch-interaction behavior for active smartphone authentication," IEEE Trans. Information Forensics and Security, vol. 11, no. 3, pp. 498-513, 2016. DOI: http://doi.org/10.1109/TIFS.2015.2503258
  12. A. Luca, A. Hang, F. Brudy, C. Lindner, and H. Hussmann, "Touch me once and I know it's you!: implicit authentication based on touch screen patterns," in Proc. ACM SIGCHI Conf. on Human Factors in Computing Systems, pp. 987-996, 2012. DOI: http://doi.org/10.1145/2207676.2208544
  13. J. Fierrez, A. Pozo, M. Martinez-Diaz, J. Galbally and A. Morales, "Benchmarking touchscreen biometrics for mobile authentication," IEEE Trans. Information Forensics and Security, vol. 13, no. 11, pp. 2720-2733, 2018. DOI: http://doi.org/10.1109/TIFS.2018.2833042.
  14. N. Sae-Bae, K. Ahmed, K. Isbister and N. Memon, "Biometric-rich gestures: A novel approach to authentication on multi-touch devices," in Proc. ACM SIGCHI Conf. on Human Factors in Computing Systems, pp. 977-986, 2012. DOI: http://doi.org/10.1145/2207676.2208543
  15. M. Frank, R. Biedert, E. Ma, I. Martinovic and D. Song, "Touchalytics: On the applicability of touchscreen input as a behavioral biometric for continuous authentication," IEEE Trans. Information Forensics Security, vol. 8, no. 1, pp. 136-148, 2013. DOI: http://doi.org/10.1109/TIFS.2012.2225048
  16. R. Murmuria, A. Stavrou, D. Barbara and D. Fleck, "Continuous authentication on mobile devices using power consumption touch gestures and physical movement of users," in Proc. Int. Workshop Recent Advances in Intrusion Detection, pp. 405-424, 2015. DOI: http://doi.org/10.1007/978-3-319-26362-5_19
  17. P. Perera and V. M. Patel, "Efficient and low latency detection of intruders in mobile active authentication," IEEE Trans. Information Forensics Security, vol. 13, no. 6, pp. 1392-1405, 2018. DOI: http://doi.org/10.1109/TIFS.2017.2787995