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Why Do People Pay for Privacy-Enhancing Technologies? The Case of Tor and JonDonym

  • David HarborthEmail author
  • Xinyuan Cai
  • Sebastian Pape
Conference paper
Part of the IFIP Advances in Information and Communication Technology book series (IFIPAICT, volume 562)

Abstract

Today’s environment of data-driven business models relies heavily on collecting as much personal data as possible. One way to prevent this extensive collection, is to use privacy-enhancing technologies (PETs). However, until now, PETs did not succeed in larger consumer markets. In addition, there is a lot of research determining the technical properties of PETs, i.e. for Tor, but the use behavior of the users and, especially, their attitude towards spending money for such services is rarely considered. Yet, determining factors which lead to an increased willingness to pay (WTP) for privacy is an important step to establish economically sustainable PETs. We argue that the lack of WTP for privacy is one of the most important reasons for the non-existence of large players engaging in the offering of a PET. The relative success of services like Tor corroborates this claim since this is a service without any monetary costs attached. Thus, we empirically investigate the drivers of active users’ WTP of a commercial PET - JonDonym - and compare them with the respective results for a donation-based service - Tor. Furthermore, we provide recommendations for the design of tariff schemes for commercial PETs.

Keywords

Privacy Privacy-enhancing technologies Pricing Willingness to pay Tor JonDonym 

References

  1. 1.
    Ball, J.: Hacktivists in the frontline battle for the internet. https://www.theguardian.com/technology/2012/apr/20/hacktivists-battle-internet
  2. 2.
    Bédard, M.: The Underestimated Economic Benefits of the Internet. In: Regulation Series. The Montreal Economic Institute (2016)Google Scholar
  3. 3.
    van Blarkom, G.W., Borking, J.J., Olk, J.G.E.: PET: Handbook of Privacy and Privacy-Enhancing Technologies (2003)Google Scholar
  4. 4.
    The Tor Project: Tor. https://www.torproject.org
  5. 5.
    JonDos Gmbh: Official Homepage of JonDonym. https://www.anonym-surfen.de
  6. 6.
    Saleh, S., Qadir, J., Ilyas, M.U.: Shedding light on the dark corners of the internet: A survey of tor research. J. Netw. Comput. Appl. 114, 1–28 (2018)CrossRefGoogle Scholar
  7. 7.
    Montieri, A., Ciuonzo, D., Aceto, G., Pescapé, A.: Anonymity services Tor, I2P, JonDonym: classifying in the dark. In: International Teletraffic Congress, pp. 81–89 (2017)Google Scholar
  8. 8.
    Pfitzmann, A., Hansen, M.: A terminology for talking about privacy by data minimization: anonymity, unlinkability, undetectability, unobservability, pseudonymity, and identity management, pp. 1–98. Tech. Univ. Dresden (2010)Google Scholar
  9. 9.
    Rossnagel, H.: The market failure of anonymity services. In: Samarati, P., Tunstall, M., Posegga, J., Markantonakis, K., Sauveron, D. (eds.) WISTP 2010. LNCS, vol. 6033, pp. 340–354. Springer, Heidelberg (2010).  https://doi.org/10.1007/978-3-642-12368-9_28CrossRefGoogle Scholar
  10. 10.
    Grossklags, J., Acquisti, A.: When 25 cents is too much: an experiment on willingness-to-sell and willingness-to-protect personal information. In: WEIS (2007)Google Scholar
  11. 11.
    Beresford, A.R., Kübler, D., Preibusch, S.: Unwillingness to pay for privacy: a field experiment. Econ. Lett. 117, 25–27 (2012)CrossRefGoogle Scholar
  12. 12.
    Borking, J.J., Raab, C.: Laws, PETs and other technologies for privacy protection. J. Inf. Law Technol. 1, 1–14 (2001)Google Scholar
  13. 13.
    Fabian, B., Goertz, F., Kunz, S., Müller, S., Nitzsche, M.: Privately waiting – a usability analysis of the tor anonymity network. In: Nelson, M.L., Shaw, M.J., Strader, T.J. (eds.) AMCIS 2010. LNBIP, vol. 58, pp. 63–75. Springer, Heidelberg (2010).  https://doi.org/10.1007/978-3-642-15141-5_6CrossRefGoogle Scholar
  14. 14.
    Singh, R., et al.: Characterizing the nature and dynamics of Tor exit blocking. In: 26th USENIX Security Symposium (USENIX Security), Vancouver, BC, pp. 325–341 (2017)Google Scholar
  15. 15.
    Chirgwin, R.: CloudFlare shows Tor users the way out of CAPTCHA hell. https://www.theregister.co.uk/2016/10/05/cloudflare_tor/
  16. 16.
    Spiekermann, S.: The desire for privacy: insights into the views and nature of the early adopters of privacy services. Int. J. Technol. Hum. Interact. 1, 74–83 (2005)CrossRefGoogle Scholar
  17. 17.
    Alsabah, M., Goldberg, I.: Performance and security improvements for tor: a survey. ACM Comput. Surv. (CSUR) 49(2), 1–36 (2016). Article no. 32CrossRefGoogle Scholar
  18. 18.
    Koch, R., Golling, M., Rodosek, G.D.: How anonymous is the tor network? A long-term black-box investigation. Computer (Long. Beach. Calif.) 49, 42–49 (2016)Google Scholar
  19. 19.
    Juarez, M., Elahi, T., Jansen, R., Diaz, C., Galvez, R., Wright, M.: Poster: fingerprinting hidden service circuits from a tor middle relay. In: Proceedings of IEEE S&P (2017)Google Scholar
  20. 20.
    Johnson, A., Wacek, C., Jansen, R., Sherr, M., Syverson, P.: Users get routed: traffic correlation on tor by realistic adversaries. In: ACM CCS, pp. 337–348 (2013)Google Scholar
  21. 21.
    Lee, L., Fifield, D., Malkin, N., Iyer, G., Egelman, S., Wagner, D.: A usability evaluation of tor launcher. In: Proceedings on Privacy Enhancing Technologies, pp. 90–109 (2017)CrossRefGoogle Scholar
  22. 22.
    Herrmann, D., Lindemann, J., Zimmer, E., Federrath, H.: Anonymity online for everyone: what is missing for zero-effort privacy on the internet? In: Camenisch, J., Kesdoğan, D. (eds.) iNetSec 2015. LNCS, vol. 9591, pp. 82–94. Springer, Cham (2016).  https://doi.org/10.1007/978-3-319-39028-4_7CrossRefGoogle Scholar
  23. 23.
    Harborth, D., et al.: Integrating privacy-enhancing technologies into the internet infrastructure. arXiv Prepr. arXiv:1711.07220 (2017)
  24. 24.
    Harborth, D., Pape, S.: JonDonym users’ information privacy concerns. In: Janczewski, L.J., Kutyłowski, M. (eds.) SEC 2018. IAICT, vol. 529, pp. 170–184. Springer, Cham (2018).  https://doi.org/10.1007/978-3-319-99828-2_13CrossRefGoogle Scholar
  25. 25.
    Harborth, D., Pape, S.: Examining technology use factors of privacy-enhancing technologies: the role of perceived anonymity and trust. In: Twenty-Fourth Americas Conference on Information Systems, New Orleans, USA (2018)Google Scholar
  26. 26.
    Harborth, D., Pape, S.: How privacy concerns and trust and risk beliefs influence users’ intentions to use privacy-enhancing technologies - the case of tor. In: Hawaii International Conference on System Sciences Proceedings, Hawaii, US (2019)Google Scholar
  27. 27.
    Malhotra, N.K., Kim, S.S., Agarwal, J.: Internet users’ information privacy concerns: the construct, the scale, and a causal model. Inf. Syst. Res. 15, 336–355 (2004)CrossRefGoogle Scholar
  28. 28.
    Grossklags, J.: Experimental economics and experimental computer science: a survey. In: Workshop on Experimental Computer Science, ExpCS 2007 (2007)Google Scholar
  29. 29.
    Acquisti, A.: The economics of personal data and the economics of privacy. In: Texte La Conférence Donnée En Décembre, pp. 1–24 (2010)Google Scholar
  30. 30.
    Benndorf, V., Normann, H.T.: The willingness to sell personal data. Scand. J. Econ. 120, 1260–1278 (2018)CrossRefGoogle Scholar
  31. 31.
    Li, C., Li, D.Y., Miklau, G., Suciu, D.: A theory of pricing private data. ACM Trans. Database Syst. (TODS) 39(4), 1–28 (2014). Article no. 34MathSciNetCrossRefGoogle Scholar
  32. 32.
    Preibusch, S.: The value of privacy in web search. In: WEIS (2013)Google Scholar
  33. 33.
    Cofone, I.N.: The value of privacy: keeping the money where the mouth is. In: 14th Annual Workshop on the Economics of Information Security, pp. 1–31 (2015)Google Scholar
  34. 34.
    Malgieri, G., Custers, B.: Pricing privacy - the right to know the value of your personal data. Comput. Law Secur. Rev. 34(2), 289–303 (2018)CrossRefGoogle Scholar
  35. 35.
    Cranor, L.F., Arjula, M., Guduru, P.: Use of a P3P user agent by early adopters. In: Proceedings of the ACM Workshop on Privacy in the Electronic Society, WPES 2002, pp. 1–10 (2002)Google Scholar
  36. 36.
    Federrath, H.: Privacy enhanced technologies: methods – markets – misuse. In: Katsikas, S., López, J., Pernul, G. (eds.) TrustBus 2005. LNCS, vol. 3592, pp. 1–9. Springer, Heidelberg (2005).  https://doi.org/10.1007/11537878_1CrossRefGoogle Scholar
  37. 37.
    Schomakers, E.M., Lidynia, C., Vervier, L., Ziefle, M.: Of guardians, cynics, and pragmatists - a typology of privacy concerns and behavior. In: IoTBDS, pp. 153–163 (2018)Google Scholar
  38. 38.
    Roßnagel, H., Zibuschka, J., Pimenides, L., Deselaers, T.: Facilitating the adoption of tor by focusing on a promising target group. In: Jøsang, A., Maseng, T., Knapskog, S.J. (eds.) NordSec 2009. LNCS, vol. 5838, pp. 15–27. Springer, Heidelberg (2009).  https://doi.org/10.1007/978-3-642-04766-4_2CrossRefGoogle Scholar
  39. 39.
    Böhme, R., Koble, S.: On the viability of privacy-enhancing technologies in a self-regulated business-to-consumer market: will privacy remain a luxury good? Dresden (2007)Google Scholar
  40. 40.
    Wilcoxon, F.: Individual comparisons by ranking methods. Biom. Bull. 1, 80–83 (1945)CrossRefGoogle Scholar
  41. 41.
    Mann, H.B., Whitney, D.R.: On a test of whether one of two random variables is stochastically larger than the other. Ann. Math. Stat. 18, 50 (1947)MathSciNetCrossRefGoogle Scholar
  42. 42.
    Benjamini, Y.: Opening the box of a boxplot. Am. Stat. 42, 257–262 (1988)Google Scholar
  43. 43.
    McKelvey, D., Zavorina, W.: A statistical model for the analysis of ordinal level dependent variables. J. Math. Sociol. 4, 103–120 (1975)MathSciNetCrossRefGoogle Scholar
  44. 44.
    Donthu, N., Gilliland, D.: Observations: the infomercial shopper. J. Advert. Res. 36, 69–76 (1996)Google Scholar
  45. 45.
    Frik, A., Gaudeul, A.: The relation between privacy protection and risk attitudes, with a new experimental method to elicit the implicit monetary value of privacy. CEGE discussion papers, Number 296. SSRN (2016). http://papers.ssrn.com/abstract=2874202
  46. 46.
    Christofides, E., Muise, A., Desmarais, S.: Risky disclosures on Facebook: the effect of having a bad experience on online behavior. J. Adolesc. Res. 27, 714–731 (2012)CrossRefGoogle Scholar
  47. 47.
    Pavlou, P.A.: Consumer acceptance of electronic commerce: integrating trust and risk with the technology acceptance model. Int. J. Electron. Commer. 7, 101–134 (2003)CrossRefGoogle Scholar
  48. 48.
    Harborth, D., Pape, S.: Explaining technology use behaviors of privacy-enhancing technologies: the case of Tor and JonDonym. Submitted to IEEE European Symposium on Security and Privacy (EuroS&P 2019) (2019)Google Scholar
  49. 49.
    Harborth, D., Pape, S.: German translation of the concerns for information privacy (CFIP) construct. SSRN (2018). https://ssrn.com/abstract=3112207
  50. 50.
    Schmitz, C.: LimeSurvey Project Team. http://www.limesurvey.org. Accessed 12 Dec 2018

Copyright information

© IFIP International Federation for Information Processing 2019

Authors and Affiliations

  1. 1.Chair of Mobile Business and Multilateral SecurityGoethe University FrankfurtFrankfurt am MainGermany

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