Abstract
Current authentication systems in vehicles use portable keys or biometric and/or touch based inputs. They can be outwitted by stealing the keys or by copying the biometric information and analyzing the touch marks. This has to be inhibited, since vehicles are not only an expensive property, that would be lost in non-authenticated hands, but wrong permitted access also can unleash heavy machine power to inexperienced drivers or even people without a driver’s license. We present a system that authenticates drivers and unlocks personalization features without any portable keys or touching. Moreover, it is invisibly integrated into a vehicle structure, the steering wheel. In contrast to biometric authentication, the password pattern is adjustable and changeable. With the presented system, vehicle manufactures are able to install driver authentication systems without any visible design changes. The manufacturer thus provides more freedom and responsibility to the driver by giving him the option to choose his own unlock pattern. Still, the security is increased by avoiding common vulnerabilities like smudge attacks, the stealing of keys, or copying of biometric data. Our experiments show excellent recognition rates for multiple string patterns. A small user study shows that our system achieves 86% accuracy for inexperienced users, up to 96% for experienced ones. The users appreciated the easy of use.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Alsaadi, I.M.: Physiological biometric authentication systems, advantages disadvantages and future development: A review. Int. J. Sci. Technol. Res. 4(12), 285–289 (2015)
Aviv, A.J., Gibson, K.L., Mossop, E., Blaze, M., Smith, J.M.: Smudge attacks on smartphone touch screens. In: 4th USENIX Workshop on Offensive Technologies, WOOT 2010 (2010)
Bowyer Jr., K.W., Doyle, J.S.: Cosmetic contact lenses and iris recognition spoofing. IEEE Comput. 47(5), 96–98 (2014)
Braun, A., Frank, S., Majewski, M., Wang, X.: CapSeat: capacitive proximity sensing for automotive activity recognition. In: Proceedings of the 7th AutomotiveUI 2015, pp. 225–232 (2015)
Braun, A., Frank, S., Wichert, R.: The capacitive chair. In: Streitz, N., Markopoulos, P. (eds.) DAPI 2015. LNCS, vol. 9189, pp. 397–407. Springer, Cham (2015). doi:10.1007/978-3-319-20804-6_36
Braun, A., Neumann, S., Schmidt, S., Wichert, R., Kuijper, A.: Towards interactive car interiors: the active armrest. In: Proceedings of the 8th Nordic Conference on Human-Computer Interaction: Fun, Fast, Foundational, pp. 911–914 (2014)
Braun, A., Wichert, R., Frank, S.: Verfahren zur feststellung der identität einer person auf einem sitz eines fahrzeugs, Patent DE 102014214978 A1, 04 Feb 2016
Braun, A., Wichert, R., Kuijper, A., Fellner, D.W.: Capacitive proximity sensing in smart environments. J. Ambient Intell. Smart Environ. 7(4), 483–510 (2015)
Ford: Ford MyKey, now on 6 million vehicles, helps parents keep teens safe this summer, June 2013
Garcia, F.D., Oswald, D., Kasper, T., Pavlidès, P.: Lock it and still lose it - on the (in)security of automotive remote keyless entry systems. In: 25th USENIX Security Symposium, USENIX Security 2016 (2016)
Grosse-Puppendahl, T., Braun, A., Kamieth, F., Kuijper, A.: Swiss-cheese extended: an object recognition method for ubiquitous interfaces based on capacitive proximity sensing. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pp. 1401–1410. ACM (2013)
Grosse-Puppendahl, T., Herber, S., Wimmer, R., Englert, F., Beck, S., von Wilmsdorff, J., Wichert, R., Kuijper, A.: Capacitive near-field communication for ubiquitous interaction and perception. In: Proceedings of the 2014 ACM International Joint Conference on Pervasive and Ubiquitous Computing, pp. 231–242 (2014)
Min, R., Choi, J., Medioni, G.G., Dugelay, J.: Real-time 3d face identification from a depth camera. In: Proceedings of the 21st International Conference on Pattern Recognition, ICPR 2012, pp. 1739–1742 (2012)
NHTSA - National Center for Statistics, Analysis: An exploration of vehicle based monitoring of novice teen drivers: Final report (2010)
NHTSA - National Center for Statistics, Analysis: Traffic safety facts - speeding (2014)
NHTSA - National Center for Statistics, Analysis: Traffic safety facts - distracted driving 2014 (2016)
Rieth, P., Böhm, J., Linkenbach, S., Hoffmann, O., Nell, J., Schirling, A., Netz, A., Stauder, P., Kuhn, M.: Steering handle for motor vehicles and method for recording a physical parameter on a steering handle, US Patent 7,321,311, 22 Jan 2008
Rus, S., Sahbaz, M., Braun, A., Kuijper, A.: Design factors for flexible capacitive sensors in ambient intelligence. In: 12th European Conference on Ambient Intelligence AmI 2015, pp. 77–92 (2015)
Schneegass, S., Steimle, F., Bulling, A., Alt, F., Schmidt, A.: SmudgeSafe: geometric image transformations for smudge-resistant user authentication. In: The 2014 ACM Conference on Ubiquitous Computing, UbiComp 2014, pp. 775–786 (2014)
Singh, G., Kumar, C.J., Rani, R.: Performance analysis of different classifiers for recognition of handwritten Gurmukhi characters using hybrid features. In: International Conference on Computing, Communication Automation, pp. 1091–1095 (2015)
Sun, C., Wang, Y., Zheng, J.: Dissecting pattern unlock: the effect of pattern strength meter on pattern selection. J. Inf. Secur. Appl. 19(4–5), 308–320 (2014)
Xia, Z., Lv, R., Zhu, Y., Ji, P., Sun, H., Shi, Y.Q.: Fingerprint liveness detection using gradient-based texture features. Signal Image Video Process. 11, 381–388 (2016)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2017 Springer International Publishing AG
About this paper
Cite this paper
Frank, S., Kuijper, A. (2017). AuthentiCap - A Touchless Vehicle Authentication and Personalization System. In: Braun, A., Wichert, R., Maña, A. (eds) Ambient Intelligence. AmI 2017. Lecture Notes in Computer Science(), vol 10217. Springer, Cham. https://doi.org/10.1007/978-3-319-56997-0_4
Download citation
DOI: https://doi.org/10.1007/978-3-319-56997-0_4
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-56996-3
Online ISBN: 978-3-319-56997-0
eBook Packages: Computer ScienceComputer Science (R0)
