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Captcha Your Location Proof—A Novel Method for Passive Location Proofs in Adversarial Environments

  • Dominik BucherEmail author
  • David Rudi
  • René Buffat
Conference paper
Part of the Lecture Notes in Geoinformation and Cartography book series (LNGC)

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.

Notes

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).

References

  1. 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
  2. Brands S, Chaum D (1994) Distance-bounding protocols. Lect Notes Comput Sci 765:344–359CrossRefGoogle Scholar
  3. 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
  4. 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. ACMGoogle Scholar
  5. 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. CiteseerGoogle Scholar
  6. Gao H, Lewis RM, Li Q (2012) Location proof via passive RFID tags. Springer, Berlin, Heidelberg, pp 500–511Google Scholar
  7. 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
  8. 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 429–430Google Scholar
  9. 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 477–485Google Scholar
  10. 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 146–162Google Scholar
  11. 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
  12. 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
  13. Mayzlin D, Dover Y, Chevalier J (2014) Promotional reviews: an empirical investigation of online review manipulation. Am Econ Rev 104(8):2421–2455CrossRefGoogle Scholar
  14. Mengjun L, Shubo L, Rui Z, Yongkai L, Jun W, Hui C (2016) Privacy-preserving distributed location proof generating system. China Commun 13(3):203–218CrossRefGoogle Scholar
  15. Miller HJ (2005) A measurement theory for time geography. Geogr Anal 37(1):17–45CrossRefGoogle Scholar
  16. 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
  17. 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
  18. 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 1–8Google Scholar
  19. 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 294–311Google Scholar
  20. Wang X, Pande A, Zhu J, Mohapatra P (2016) Stamp: enabling privacy-preserving location proofs for mobile users. IEEE/ACM Trans Netw 24(6):3276–3289CrossRefGoogle Scholar
  21. Waters B, Felten E (2003) Proving the location of tamper-resistant devices. Technical ReportGoogle Scholar
  22. Waters B, Felten E (2003) Secure, private proofs of location. Technical reportGoogle Scholar
  23. 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 271–280Google Scholar
  24. 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
  25. 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 1889–1897Google Scholar

Copyright information

© Springer International Publishing AG 2018

Authors and Affiliations

  1. 1.Institute of Cartography and GeoinformationETH ZurichZurichSwitzerland

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