Advertisement

Incognitus: Privacy-Preserving User Interests in Online Social Networks

  • Alexandros KornilakisEmail author
  • Panagiotis Papadopoulos
  • Evangelos Markatos
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11398)

Abstract

Online Social Networks have changed the way we reach news and information. An increasing number of people use social networks not only for communicating with friends and colleagues but also for their daily information needs. Apart from providing the users with personalized information in a timely manner, this functionality may also raise significant privacy concerns. The service provider is able to observe both the Pages a user is subscribed to and her inter- actions with them. The collected data can form a detailed user profile, which can later be used for several purposes; usually beyond the control of the user. To ad- dress these privacy concerns, we propose Incognitus: an approach to allow users browse Pages of OSNs without disclosing their interests or activity to the service provider. Our approach provides (i) a incognito mode of operation when browsing privacy-sensitive content. In this isolated, offline mode no tracking mechanisms can monitor the users behavior and no information can be leaked to the provider. At the same time, (ii) by using an obfuscation-based mechanism, Incognitus reduces the accuracy of the service provider when monitoring the interests of a user. Early results show that Incognitus has minimal bandwidth requirements and imposes reasonable latency to the users browsing experience.

Notes

Acknowledgement

The research leading to these results has received funding from European Unions Marie Sklodowska-Curie grant agreement No 690972. The paper reflects only the authors view and the Agency and the Commission are not responsible for any use that may be made of the information it contains.

References

  1. 1.
  2. 2.
    Acar, G., Eubank, C., Englehardt, S., Juarez, M., Narayanan, A., Diaz, C.: The web never forgets: persistent tracking mechanisms in the wild. In: Proceedings of the 2014 ACM SIGSAC Conference on CCS (2014)Google Scholar
  3. 3.
    Balsa, E., Troncoso, C., Diaz, C.: OB-PWS: Obfuscation-based private web search. In: IEEE Symposium on S&P 2012 (2012)Google Scholar
  4. 4.
    Brown, M.S.: When and where to buy consumer data (and 12 companies who sell it) (2015). http://www.forbes.com/sites/metabrown/2015/09/30/when-and-where-to-buy-consumer-data-and-12-companies-who-sell-it
  5. 5.
    Dingledine, R., Mathewson, N., Syverson, P.: Tor: the second-generation onion router. In: Proceedings of the 13th Conference on USENIX Security Symposium, SSYM 2004, Berkeley, CA, USA, vol. 13, pp. 21. USENIX Association (2004)Google Scholar
  6. 6.
    Drake, N.: Help, I’m trapped in Facebook’s absurd pseudonym purgatory (2015). http://www.wired.com/2015/06/facebook-real-name-policy-problems
  7. 7.
    Eckersley, P.: How unique is your web browser? In: Atallah, M.J., Hopper, N.J. (eds.) PETS 2010. LNCS, vol. 6205, pp. 1–18. Springer, Heidelberg (2010).  https://doi.org/10.1007/978-3-642-14527-8_1CrossRefGoogle Scholar
  8. 8.
    Elovici, Y., Shapira, B., Meshiach, A.: Cluster-analysis attack against a private web solution (PRAW). Online Inf. Rev. 30(6), 624–643 (2006)CrossRefGoogle Scholar
  9. 9.
    Facebook business. Facebook pages (2017). https://www.facebook.com/business/products/pages
  10. 10.
    Facebook for developers. Facebook platform policy (2016). https://developers.facebook.com/policy/
  11. 11.
    Facebook for developers. Facebook developer documentation (2017). https://developers.facebook.com/docs/
  12. 12.
    Greenberg, A.: Why Facebook just launched its own “dark web” site (2014). https://www.wired.com/2014/10/facebook-tor-dark-site/
  13. 13.
    Howe, D.C., Nissenbaum, H.: TrackMeNot: resisting surveillance in web search. In: Lessons from the Identity Trail: Anonymity, Privacy, and Identity in a Networked Society, vol. 23, pp. 417–436 (2009)Google Scholar
  14. 14.
    Facebook Inc.: Facebook login (2018). https://developers.facebook.com/docs/facebook-login/
  15. 15.
    Johansson, F., Kaati, L., Shrestha, A.: Timeprints for identifying social media users with multiple aliases. Secur. Inf. 4(1), 1 (2015)CrossRefGoogle Scholar
  16. 16.
    Kamkar, S.: Evercookie - virtually irrevocable persistent cookies (2010). http://samy.pl/evercookie/
  17. 17.
    Kontaxis, G., Polychronakis, M., Markatos, E.P.: Minimizing information disclosure to third parties in social login platforms. Int. J. Inf. Secur. 11(5), 321–332 (2012)CrossRefGoogle Scholar
  18. 18.
    Krug, S.: Reactions now available globally (2016). https://newsroom.fb.com/news/2016/02/reactions-now-available-globally/
  19. 19.
    Kumar, M.: Why Facebook is buying Whatsapp for \$19 billion? (2014). http://thehackernews.com/2014/02/why-facebook-is-buying-whatsapp-for-19.html
  20. 20.
    Li, N., Li, T., Venkatasubramanian, S.: t-closeness: privacy beyond k-anonymity and l-diversity. In: 2007 IEEE 23rd International Conference on Data Engineering, pp. 106–115. IEEE (2007)Google Scholar
  21. 21.
    Machanavajjhala, A., Kifer, D., Gehrke, J., Venkitasubramaniam, M.: l-diversity: privacy beyond k-anonymity. ACM Trans. Knowl. Discov. Data (TKDD) 1(1), 3 (2007)CrossRefGoogle Scholar
  22. 22.
    Mander, J.: Why Facebook is tracking time spent on newsfeeds (2015). http://www.globalwebindex.net/blog/why-facebook-is-tracking-time-spent-on-newsfeeds
  23. 23.
    Mozilla developer network and individual contributors. Add-on SDK (2016). https://developer.mozilla.org/en-US/Add-ons/SDK
  24. 24.
    Papadopoulos, E.P., Diamantaris, M., Papadopoulos, P., Petsas, T., Ioannidis, S., Markatos, E.P.: The long-standing privacy debate: mobile websites vs mobile apps. In: Proceedings of the 26th International Conference on World Wide Web, WWW 2017, Republic and Canton of Geneva, Switzerland, pp. 153–162. International World Wide Web Conferences Steering Committee (2017)Google Scholar
  25. 25.
    Papadopoulos, P., Chariton, A.A., Athanasopoulos, E., Markatos, E.P.: Where’s Wally? How to privately discover your friends on the internet. In: Proceedings of the ASIACCS 2018 (2018)Google Scholar
  26. 26.
    Papadopoulos, P., Kourtellis, N., Markatos, E.P.: Cookie synchronization: everything you always wanted to know but were afraid to ask. arXiv preprint arXiv:1805.10505 (2018)
  27. 27.
    Papadopoulos, P., Kourtellis, N., Markatos, E.P.: Exclusive: how the (synced) cookie monster breached my encrypted VPN session. In: Proceedings of the 11th European Workshop on Systems Security, EuroSec 2018 (2018)Google Scholar
  28. 28.
    Papadopoulos, P., Papadogiannakis, A., Polychronakis, M., Zarras, A., Holz, T., Markatos, E.P.: K-subscription: privacy-preserving microblogging browsing through obfuscation. In: Proceedings of the ACSAC 2013 (2013)Google Scholar
  29. 29.
    RT. Privacy betrayed: Twitter sells multi-billion tweet archive (2012). https://www.rt.com/news/twitter-sells-tweet-archive-529/
  30. 30.
    Shearer, E., Gottfried, J.: News use across social media platforms (2017). http://www.journalism.org/2017/09/07/news-use-across-social-media-platforms-2017/
  31. 31.
    Singer, N., Merrill, J.B.: When a company is put up for sale, in many cases, your personal data is, too (2015). http://www.nytimes.com/2015/06/29/technology/when-a-company-goes-up-for-sale-in-many-cases-so-does-your-personal-data.html
  32. 32.
    Solon, O.: Facebook says Cambridge Analytica may have gained 37m more users’ data (2018). https://www.theguardian.com/technology/2018/apr/04/facebook-cambridge-analytica-user-data-latest-more-than-thought
  33. 33.
    Sweeney, L.: k-anonymity: a model for protecting privacy. Int. J. Uncertainty Fuzziness Knowl. Based Syst. 10(05), 557–570 (2002)MathSciNetCrossRefGoogle Scholar
  34. 34.
    Wakefield, J.: Social media ‘outstrips TV’ as news source for young people, June 2016. https://www.bbc.com/news/uk-36528256
  35. 35.
    Weinstein, R.: Mutation summary (2015). https://github.com/rafaelw/mutation-summary
  36. 36.
    Youyou, W., Kosinski, M., Stillwell, D.: Computer-based personality judgments are more accurate than those made by humans. Proc. Nat. Acad. Sci. 112(4), 1036–1040 (2015)CrossRefGoogle Scholar

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Alexandros Kornilakis
    • 1
    Email author
  • Panagiotis Papadopoulos
    • 1
  • Evangelos Markatos
    • 1
  1. 1.FORTH-ICSHeraklionGreece

Personalised recommendations