346
Views
0
CrossRef citations to date
0
Altmetric
Research Articles

PushPIN: A Pressure-Based Behavioral Biometric Authentication System for Smartwatches

ORCID Icon & ORCID Icon
Pages 893-909 | Received 19 Aug 2021, Accepted 01 Mar 2022, Published online: 19 Apr 2022

References

  • Accot, J., & Zhai, S. (2003). Refining fitts’ law models for bivariate pointing. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (pp. 193–200). Association for Computing Machinery. https://doi.org/10.1145/642611.642646
  • Adapa, A., Nah, F. F.-H., Hall, R. H., Siau, K., & Smith, S. N. (2018). Factors influencing the adoption of smart wearable devices. International Journal of Human–Computer Interaction, 34(5), 399–409. https://doi.org/10.1080/10447318.2017.1357902
  • Anwar, M., & Imran, A. (2015). A comparative study of graphical and alphanumeric passwords for mobile device authentication. In M. Glass & J. H. Kim (Eds.), Proceedings of the 26th Modern AI and Cognitive Science Conference 2015, Greensboro, NC, USA, April 25–26, 2015 (Vol. 1353, pp. 13–18). CEUR-WS.org. http://ceur-ws.org/Vol-1353/paper_11.pdf
  • Bangor, A., Kortum, P., & Miller, J. (2009). Determining what individual SUS scores mean: Adding an adjective rating scale. The Journal of Usability Studies, 4(3), 114–123. https://dl.acm.org/doi/10.5555/2835587.2835589
  • Beyan, C., Zunino, A., Shahid, M., & Murino, V. (2021). Personality traits classification using deep visual activity-based nonverbal features of key-dynamic images. IEEE Transactions on Affective Computing, 12(4), 1084–1099. https://doi.org/10.1109/TAFFC.2019.2944614
  • Bianchi, A., Oakley, I., & Kwon, D. S. (2012). Counting clicks and beeps: Exploring numerosity based haptic and audio PIN entry. Interacting with Computers, 24(5), 409–422. https://doi.org/10.1016/j.intcom.2012.06.005
  • Bonneau, J., Preibusch, S., & Anderson, R. (2012). A birthday present every eleven wallets? The security of customer-chosen banking pins. In A. D. Keromytis (Ed.), Financial cryptography and data security (pp. 25–40). Springer Berlin Heidelberg.
  • Brewster, S. A., & Hughes, M. (2009). Pressure-based text entry for mobile devices. In Proceedings of the 11th International Conference on Human-Computer Interaction with Mobile Devices and Services. Association for Computing Machinery. https://doi.org/10.1145/1613858.1613870
  • Buriro, A., Crispo, B., & Conti, M. (2019). ANSWERAUTH: A bimodal behavioral biometric-based user authentication scheme for smartphones. Journal of Information Security and Applications, 44, 89–103. https://doi.org/10.1016/j.jisa.2018.11.008
  • Buriro, A., Crispo, B., Delfrari, F., & Wrona, K. (2016). Hold and sign: A novel behavioral biometrics for smartphone user authentication. In 2016 IEEE Security and Privacy Workshops. IEEE.
  • Buriro, A., Van Acker, R., Crispo, B., & Mahboob, A. (2018). Airsign: A gesture-based smartwatch user authentication. In 2018 International Carnahan Conference on Security Technology (ICCST) (pp. 1–5). IEEE. https://doi.org/10.1109/CCST.2018.8585571
  • Cho, G., Huh, J. H., Cho, J., Oh, S., Song, Y., & Kim, H. (2017). Syspal: System-guided pattern locks for android. In 2017 IEEE Symposium on Security and Privacy (SP) (pp. 338–356). IEEE. https://doi.org/10.1109/SP.2017.61
  • De Luca, A., Hang, A., Brudy, F., Lindner, C., & Hussmann, H. (2012). Touch me once and i know it’s you! implicit authentication based on touch screen patterns. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (pp. 987–996). Association for Computing Machinery. https://doi.org/10.1145/2207676.2208544
  • Fortify, H. (2015). Internet of things security study: Smartwatches. Technical report, HP. https://www.ftc.gov/system/files/documents/public_comments/2015/10/00050-98093.pdf
  • Gil, H., Lee, D., Im, S., & Oakley, I. (2017). Tritap: Identifying finger touches on smartwatches. In Proceedings of the 2017 CHI Conference on Human Factors in Computing Systems (pp. 3879–3890). Association for Computing Machinery. https://doi.org/10.1145/3025453.3025561
  • Goguey, A., Malacria, S., & Gutwin, C. (2018). Improving discoverability and expert performance in force-sensitive text selection for touch devices with mode gauges. In Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems (pp. 1–12). Association for Computing Machinery. https://doi.org/10.1145/3173574.3174051
  • Hart, S. G., Staveland, L. E. (1988). Development of nasa-tlx (task load index): Results of empirical and theoretical research. In P. A. Hancock & N. Meshkati (Eds.), Human mental workload (Vol. 52, pp. 139–183). North-Holland. https://www.sciencedirect.com/science/article/pii/S0166411508623869
  • Hutchins, B., Reddy, A., Jin, W., Zhou, M., Li, M., & Yang, L. (2018). Beat-pin: A user authentication mechanism for wearable devices through secret beats. In Proceedings of the 2018 on Asia Conference on Computer and Communications Security (pp. 101–115). Association for Computing Machinery. https://doi.org/10.1145/3196494.3196543
  • Jeong, H., Kim, H., Kim, R., Lee, U., & Jeong, Y. (2017). Smartwatch wearing behavior analysis: A longitudinal study. Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies, 1(3), 1–31. https://doi.org/10.1145/3131892
  • Khan, H., Hengartner, U., & Vogel, D. (2018). Evaluating attack and defense strategies for smartphone pin shoulder surfing. In Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems (pp. 1–10). Association for Computing Machinery. https://doi.org/10.1145/3173574.3173738
  • Knight, J. F., & Baber, C. (2007). Assessing the physical loading of wearable computers. Applied Ergonomics, 38(2), 237–247. https://doi.org/10.1016/j.apergo.2005.12.008
  • Krombholz, K., Hupperich, T., & Holz, T. (2016). Use the force: Evaluating Force-Sensitive authentication for mobile devices. In Twelfth Symposium on Usable Privacy and Security (SOUPS 2016) (pp. 207–219). USENIX Association. https://www.usenix.org/conference/soups2016/technical-sessions/presentation/krombholz
  • Li, C., Jing, J., & Liu, Y. (2021). Mobile user authentication-Turn it to unlock. In 2021 6th International Conference on Mathematics and Artificial Intelligence (ICMAI 2021) (pp. 101–107). Association for Computing Machinery. https://doi.org/10.1145/3460569.3460577
  • Li, Y., & Xie, M. (2018). Understanding secure and usable gestures for realtime motion based authentication. In IEEE INFOCOM 2018 - IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS) (pp. 13–20). IEEE. https://doi.org/10.1109/INFCOMW.2018.8406912
  • Lu, C. X., Du, B., Kan, X., Wen, H., Markham, A., & Trigoni, N. (2017). Verinet: User verification on smartwatches via behavior biometrics. In Proceedings of the First ACM Workshop on Mobile Crowdsensing Systems and Applications (pp. 68–73). Association for Computing Machinery. https://doi.org/10.1145/3139243.3139251
  • Nguyen, T., & Memon, N. (2018). Tap-based user authentication for smartwatches. Computers & Security, 78, 174–186. https://doi.org/10.1016/j.cose.2018.07.001
  • Nguyen, T., & Memon, N. D. (2017). Smartwatches locking methods: A comparative study. In Thirteenth Symposium on Usable Privacy and Security (SOUPS 2017). USENIX Association. https://www.usenix.org/conference/soups2017/workshop-program/way2017/nguyen
  • Oakley, I., Huh, J. H., Cho, J., Cho, G., Islam, R., & Kim, H. (2018). The personal identification chord: A four button authentication system for smartwatches. In Proceedings of the 2018 on Asia Conference on Computer and Communications Security (pp. 75–87). Association for Computing Machinery. https://doi.org/10.1145/3196494.3196555
  • Ranak, M. S. A. N., Azad, S., Nor, N. N. H. B. M., & Zamli, K. Z. (2017). Press touch code: A finger press based screen size independent authentication scheme for smart devices. PLoS One, 12(10), e0186940. https://doi.org/10.1371/journal.pone.0186940
  • Saad, N., & Djedi, N. (2017). Recognition of 3d faces with missing parts based on sift and lbp methods. In R. Jiang, S. Al-maadeed, A. Bouridane, P. D. Crookes, & A. Beghdadi (Eds.), Biometric security and privacy: Opportunities & challenges in the big data era (pp. 273–297). Springer International Publishing. https://doi.org/10.1007/978-3-319-47301-7_12
  • Sae-Bae, N., Ahmed, K., Isbister, K., & Memon, N. (2012). Biometric-rich gestures: A novel approach to authentication on multi-touch devices. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (pp. 977–986). Association for Computing Machinery. https://doi.org/10.1145/2207676.2208543
  • Salem, A., & Obaidat, M. S. (2019). A novel security scheme for behavioral authentication systems based on keystroke dynamics. Security and Privacy, 2(2), e64. https://doi.org/10.1002/spy2.64
  • Sasamoto, H., Christin, N., & Hayashi, E. (2008). Undercover: Authentication usable in front of prying eyes. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (pp. 183–192). Association for Computing Machinery. https://doi.org/10.1145/1357054.1357085
  • Saulynas, S., Lechner, C., & Kuber, R. (2018). Towards the use of brain–computer interface and gestural technologies as a potential alternative to pin authentication. International Journal of Human–Computer Interaction, 34(5), 433–444. https://doi.org/10.1080/10447318.2017.1357905
  • Scikit-learn (2021). 3.2. Tuning the hyper-parameters of an estimator. https://scikit-learn.org/stable/modules/grid_search.html (accessed 27 April 2021)
  • Siek, K. A., Rogers, Y., & Connelly, K. H. (2005). Fat finger worries: How older and younger users physically interact with pdas. In M. F. Costabile & F. Paternò (Eds.), Human-computer interaction - INTERACT 2005 (pp. 267–280). Springer.
  • Teh, P. S., Zhang, N., Teoh, A. B. J., & Chen, K. (2016). A survey on touch dynamics authentication in mobile devices. Computers & Security, 59, 210–235. https://doi.org/10.1016/j.cose.2016.03.003
  • Unar, J., Seng, W. C., & Abbasi, A. (2014). A review of biometric technology along with trends and prospects. Pattern Recognition, 47(8), 2673–2688. https://doi.org/10.1016/j.patcog.2014.01.016
  • Zhao, Y., Qiu, Z., Yang, Y., Li, W., & Fan, M. (2017). An empirical study of touch-based authentication methods on smartwatches. In Proceedings of the 2017 ACM International Symposium on Wearable Computers (pp. 122–125). Association for Computing Machinery. https://doi.org/10.1145/3123021.3123049

Reprints and Corporate Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

To request a reprint or corporate permissions for this article, please click on the relevant link below:

Academic Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

Obtain permissions instantly via Rightslink by clicking on the button below:

If you are unable to obtain permissions via Rightslink, please complete and submit this Permissions form. For more information, please visit our Permissions help page.