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.
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
Anderson M, Magruder J (2012) Learning from the crowd: regression discontinuity estimates of the effects of an online review database*. Econ J 122(563):957–989. http://dx.doi.org/10.1111/j.1468-0297.2012.02512.x
Brands S, Chaum D (1994) Distance-bounding protocols. Lect Notes Comput Sci 765:344–359
Brown M, Lowe DG (2007) Automatic panoramic image stitching using invariant features. Int J Comput Vis 74(1):59–73. https://doi.org/10.1007/s11263-006-0002-3
Bucher D, Scheider S, Raubal M (2017) A model and framework for matching complementary spatio-temporal needs. In: Proceedings of the 25th ACM SIGSPATIAL international conference on advances in geographic information systems. ACM
Francillon A, Danev B, Capkun S (2011) Relay attacks on passive keyless entry and start systems in modern cars. In: Proceedings of the 18th annual network and distributed system security symposium. the internet society. Citeseer
Gao H, Lewis RM, Li Q (2012) Location proof via passive RFID tags. Springer, Berlin, Heidelberg, pp 500–511
Hu N, Liu L, Sambamurthy V (2011) Fraud detection in online consumer reviews. Decis Support Syst 50(3):614–626. On quantitative methods for detection of financial fraud. http://www.sciencedirect.com/science/article/pii/S0167923610001363
Javali C, Revadigar G, Hu W, Jha S (2015) Poster: were you in the cafe yesterday?: location proof generation and verification for mobile users. In: Proceedings of the 13th ACM conference on embedded networked sensor systems. ACM, pp 429–430
Javali C, Revadigar G, Rasmussen KB, Hu W, Jha S (2016) I am Alice, I was in wonderland: secure location proof generation and verification protocol. In: 2016 IEEE 41st conference on local computer networks (LCN), Nov 2016, pp 477–485
Khan R, Zawoad S, Haque MM, Hasan R (2014) Who, when, and where? Location proof assertion for mobile devices. In: IFIP annual conference on data and applications security and privacy. Springer, pp 146–162
Lowe DG (2004) Distinctive image features from scale-invariant keypoints. Int J Comput Vis 60(2):91–110. https://doi.org/10.1023/B:VISI.0000029664.99615.94
Luo W, Hengartner U (2010) Veriplace: a privacy-aware location proof architecture. In: Proceedings of the 18th SIGSPATIAL international conference on advances in geographic information systems, GIS ’10. ACM, New York, NY, USA, pp 23–32. http://doi.acm.org/10.1145/1869790.1869797
Mayzlin D, Dover Y, Chevalier J (2014) Promotional reviews: an empirical investigation of online review manipulation. Am Econ Rev 104(8):2421–2455
Mengjun L, Shubo L, Rui Z, Yongkai L, Jun W, Hui C (2016) Privacy-preserving distributed location proof generating system. China Commun 13(3):203–218
Miller HJ (2005) A measurement theory for time geography. Geogr Anal 37(1):17–45
Saroiu S, Wolman A (2009) Enabling new mobile applications with location proofs. In: Proceedings of the 10th workshop on mobile computing systems and applications, HotMobile ’09. ACM, New York, NY, USA, pp 3:1–3:6. http://doi.acm.org/10.1145/1514411.1514414
Sastry N, Shankar U, Wagner D (2003) Secure verification of location claims. In: Proceedings of the 2nd ACM workshop on wireless security, WiSe ’03. ACM, New York, NY, USA, pp 1–10. http://doi.acm.org/10.1145/941311.941313
Talasila M, Curtmola R, Borcea C (2013) Improving location reliability in crowd sensed data with minimal efforts. In: 2013 6th Joint IFIP wireless and mobile networking conference (WMNC). IEEE, pp 1–8
Von Ahn L, Blum M, Hopper NJ, Langford J (2003) Captcha: using hard AI problems for security. In: International conference on the theory and applications of cryptographic techniques. Springer, pp 294–311
Wang X, Pande A, Zhu J, Mohapatra P (2016) Stamp: enabling privacy-preserving location proofs for mobile users. IEEE/ACM Trans Netw 24(6):3276–3289
Waters B, Felten E (2003) Proving the location of tamper-resistant devices. Technical Report
Waters B, Felten E (2003) Secure, private proofs of location. Technical report
Weiser P, Bucher D, Cellina F, De Luca V (2015) A taxonomy of motivational affordances for meaningful gamified and persuasive technologies. In: Proceedings of the 3rd international conference on ICT for sustainability (ICT4S). Advances in computer science research, vol 22. Atlantis Press, Paris, pp 271–280
Ye Q, Law R, Gu B, Chen W (2011) The influence of user-generated content on traveler behavior: an empirical investigation on the effects of e-word-of-mouth to hotel online bookings. Comput Hum Behav 27(2):634–639. Web 2.0 in travel and tourism: empowering and changing the role of travelers. http://www.sciencedirect.com/science/article/pii/S0747563210000907
Zhu Z, Cao G (2011) Applaus: a privacy-preserving location proof updating system for location-based services. In: 2011 Proceedings IEEE INFOCOM, Apr 2011, pp 1889–1897
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).
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2018 Springer International Publishing AG
About this paper
Cite this paper
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
Download citation
DOI: https://doi.org/10.1007/978-3-319-71470-7_14
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-71469-1
Online ISBN: 978-3-319-71470-7
eBook Packages: Earth and Environmental ScienceEarth and Environmental Science (R0)