Abstract
A large number of online rating and review platforms allow users to exchange their experiences with products and locations. These platforms need to implement appropriate mechanisms to counter malicious content, such as contributions which aim at either wrongly accrediting or discrediting some product or location. For ratings and reviews of locations, the aim of such a mechanism is to ensure that a user actually was at said location, and did not simply post a review from another, arbitrary location. Existing solutions usually require a costly infrastructure, need proof witnesses to be co-located with users, or suggest schemes such as users taking pictures of themselves at the location of interest. This paper introduces a method for location proofs based on visual features and image recognition, which is cheap to implement yet provides a high degree of security and tamper-resistance without placing a large burden on the user.
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Acknowledgements
This research was supported by the Swiss National Science Foundation (SNF) within NRP 71 “Managing energy consumption” and by the Commission for Technology and Innovation (CTI) within the Swiss Competence Center for Energy Research (SCCER) Mobility and FURIES (Future Swiss Electrical Infrastructure).
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Bucher, D., Rudi, D., Buffat, R. (2018). Captcha Your Location Proof—A Novel Method for Passive Location Proofs in Adversarial Environments. In: Kiefer, P., Huang, H., Van de Weghe, N., Raubal, M. (eds) Progress in Location Based Services 2018. LBS 2018. Lecture Notes in Geoinformation and Cartography. Springer, Cham. https://doi.org/10.1007/978-3-319-71470-7_14
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