The Geo-Privacy Bonus of Popular Photo Enhancements

TitleThe Geo-Privacy Bonus of Popular Photo Enhancements
Publication TypeConference Paper
Year of Publication2017
AuthorsChoi, J., Larson M., Li X., Li K., Friedland G., & Hanjalic A.
Published inProceedings of the 2017 ACM on International Conference on Multimedia Retrieval
Page(s)84-92
Abstract

Today's geo-location estimation approaches are able to infer the location of a target image using its visual content alone. These approaches typically exploit visual matching techniques, applied to a large collection of background images with known geo-locations. Users who are unaware that visual analysis and retrieval approaches can compromise their geo-privacy, unwittingly open themselves to risks of crime or other unintended consequences. This paper lays the groundwork for a new approach to geo-privacy of social images: Instead of requiring a change of user behavior, we start by investigating users' existing photo-sharing practices. We carry out a series of experiments using a large collection of social images (8.5M) to systematically analyze how photo editing practices impact the performance of geo-location estimation. We find that standard image enhancements, including filters and cropping, already serve as natural geo-privacy protectors. In our experiments, up to 19% of images whose location would otherwise be automatically predictable were unlocalizeable after enhancement. We conclude that it would be wrong to assume that geo-visual privacy is a lost cause in today's world of rapidly maturing machine learning. Instead, protecting users against the unwanted effects of pixel-based inference is a viable research field. A starting point is understanding the geo-privacy bonus of already established user behavior.

Acknowledgment

Part of the experimentation for this work was carried out on the Dutch national e-infrastructure with the support of the SURF Foundation. It was also partially supported by a National Science Foundation Grant No. CNS 1514509 and a collaborative LDRD led by Lawrence Livermore National Laboratory (U.S. Dept. of Energy contract DE-AC52-07NA27344). Any findings and conclusions are the authors’, and do not necessarily reflect the views of the funders. 

URLhttp://delivery.acm.org/10.1145/3090000/3080543/p84-choi.pdf?ip=192.150.187.235&id=3080543&acc=ACTIVE%20SERVICE&key=0A6AD1E863DA1AC4%2E4D4702B0C3E38B35%2E4D4702B0C3E38B35%2E4D4702B0C3E38B35&CFID=784904814&CFTOKEN=19011339&__acm__=1499892333_01d095b68a2a34
ICSI Research Group

Audio and Multimedia