Abstract
In the coming age of wearable computing, devices such as Google Glass will become as ubiquitous as smartphones. Their foreseeable deployment in public spaces will cause distinct implications on the privacy of people recorded by these devices. Particularly the discreet recording capabilities of such devices pose new challenges to consensual image disclosure. Therefore, new Privacy Enhancing Technologies (PETs) will be needed to help preserve our digital privacy. At the time of writing, no such PETs are available on the market to communicate privacy preferences towards Glass. In the scientific literature, a handful of approaches has been presented. However, none of them has been evaluated regarding their affordances and overall usefulness. In this paper, we provide the first systematization and qualitative evaluation of state of the art PETs that were designed to communicate privacy preferences towards (wearable) cameras, such as Google Glass. The purpose of this paper is to foster a broader discourse on how such technology should be designed in order to be fully privacy preserving and usable.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsReferences
Google Glass targeted as symbol by anti-tech crowd. http://edition.cnn.com/2014/04/14/tech/mobile/google-glass-attack/. Accessed 10 July 2014
Barhm, M.S., Qwasmi, N., Qureshi, F.Z., el-Khatib, K.: Negotiating privacy preferences in video surveillance systems. In: Mehrotra, K.G., Mohan, C.K., Oh, J.C., Varshney, P.K., Ali, M. (eds.) IEA/AIE 2011, Part II. LNCS, vol. 6704, pp. 511–521. Springer, Heidelberg (2011)
Dabrowski, A., Weippl, E.R., Echizen, I.: Framework based on privacy policy hiding for preventing unauthorized face image processing. In: 2013 IEEE International Conference on Systems, Man, and Cybernetics (SMC), pp. 455–461. IEEE (2013)
Denning, T., Dehlawi, Z., Kohno, T.: In situ with bystanders of augmented reality glasses: perspectives on recording and privacy-mediating technologies. In: Proceedings of the 32nd Annual ACM Conference on Human Factors in Computing Systems, pp. 2377–2386. ACM (2014)
Harvey, A.: CV Dazzle, 2010–2012. http://cvdazzle.com/. Accessed 10 April 2014
Henne, B., Szongott, C., Smith, M.: Snapme if you can: privacy threats of other peoples’ geo-tagged media and what we can do about it. In: Proceedings of the Sixth ACM Conference on Security and Privacy in Wireless and Mobile Networks, pp. 95–106. ACM (2013)
Pallas, F., Ulbricht, M.-R., Jaume-Palasí, L., Höppner, U.: Offlinetags: a novel privacy approach to online photo sharing. In: CHI 2014 Extended Abstracts on Human Factors in Computing Systems, CHI EA 2014, pp. 2179–2184. ACM, New York (2014)
Patel, S.N., Summet, J.W., Truong, K.N.: Blindspot: creating capture-resistant spaces. In: Senior, A. (ed.) Protecting Privacy in Video Surveillance, pp. 185–201. Springer, Heidelberg (2009)
Schiff, J., Meingast, M., Mulligan, D.K., Sastry, S., Goldberg, K.: Respectful cameras: detecting visual markers in real-time to address privacy concerns. In: Senior, A. (ed.) Protecting Privacy in Video Surveillance, pp. 65–89. Springer, Heidelberg (2009)
Templeman, R., Korayem, M., Crandall, D., Kapadia, A.: Placeavoider: steering first-person cameras away from sensitive spaces. In: Network and Distributed System Security Symposium (NDSS) (2014)
Yamada, T., Gohshi, S., Echizen, I.: Use of invisible noise signals to prevent privacy invasion through face recognition from camera images. In: Proceedings of the 20th ACM International Conference on Multimedia, MM 2012, pp. 1315–1316. ACM, New York (2012)
Yamada, T., Gohshi, S., Echizen, I.: Privacy visor: method for preventing face image detection by using differences in human and device sensitivity. In: De Decker, B., Dittmann, J., Kraetzer, C., Vielhauer, C. (eds.) CMS 2013. LNCS, vol. 8099, pp. 152–161. Springer, Heidelberg (2013)
Yus, R., Pappachan, P., Das, P.K., Mena, E., Joshi, A., Finin, T.: Demo: faceblock: privacy-aware pictures for google glass. In: Proceedings of the 12th Annual International Conference on Mobile Systems, Applications, and Services, pp. 366–366. ACM (2014)
Acknowledgements
We would like to thank Johanna Ullrich and the reviewers for their insightful comments. The research was funded by COMET K1, FFG - Austrian Research Promotion Agency.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2015 International Financial Cryptography Association
About this paper
Cite this paper
Krombholz, K., Dabrowski, A., Smith, M., Weippl, E. (2015). Ok Glass, Leave Me Alone: Towards a Systematization of Privacy Enhancing Technologies for Wearable Computing. In: Brenner, M., Christin, N., Johnson, B., Rohloff, K. (eds) Financial Cryptography and Data Security. FC 2015. Lecture Notes in Computer Science(), vol 8976. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-48051-9_20
Download citation
DOI: https://doi.org/10.1007/978-3-662-48051-9_20
Published:
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-662-48050-2
Online ISBN: 978-3-662-48051-9
eBook Packages: Computer ScienceComputer Science (R0)