Bloom Cookies: Web Search Personalization without User Tracking
Nitesh Mor, Oriana Riva, Suman Nath, John D. Kubiatowicz

Citation
Nitesh Mor, Oriana Riva, Suman Nath, John D. Kubiatowicz. "Bloom Cookies: Web Search Personalization without User Tracking". NDSS 2015, Internet Society, 8, February, 2015.

Abstract
We propose Bloom cookies that encode a user's profile in a compact and privacy-preserving way, without preventing online services from using it for personalization purposes. The Bloom cookies design is inspired by our analysis of a large set of web search logs that shows drawbacks of two profile obfuscation techniques, namely profile generalization and noise injection, today used by many privacy-preserving personalization systems. We find that profile generalization significantly hurts personalization and fails to protect users from a server linking user sessions over time. Noise injection can address these problems, but only at the cost of a high communication overhead and a noise dictionary generated by a trusted third party. In contrast, Bloom cookies leverage Bloom filters as a privacy-preserving data structure to provide a more convenient privacy, personalization, and network efficiency tradeoff: they provide similar (or better) personalization and privacy than noise injection (and profile generalization), but with an order of magnitude lower communication cost and no noise dictionary. We discuss how Bloom cookies can be used for personalized web search, present an algorithm to automatically configure the noise in Bloom cookies given a user's privacy and personalization goals, and evaluate their performance compared to the state-of-the-art.

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Citation formats

• HTML

  Nitesh Mor, Oriana Riva, Suman Nath, John D. Kubiatowicz.
  <a
  href="http://www.terraswarm.org/pubs/461.html"
  >Bloom Cookies: Web Search Personalization without User
  Tracking</a>, NDSS 2015, Internet Society, 8,
  February, 2015.

• Plain text

  Nitesh Mor, Oriana Riva, Suman Nath, John D. Kubiatowicz.
  "Bloom Cookies: Web Search Personalization without User
  Tracking". NDSS 2015, Internet Society, 8, February,
  2015.

• BibTeX

  @inproceedings{MorRivaNathKubiatowicz15_BloomCookiesWebSearchPersonalizationWithoutUserTracking,
      author = {Nitesh Mor and Oriana Riva and Suman Nath and John
                D. Kubiatowicz},
      title = {Bloom Cookies: Web Search Personalization without
                User Tracking},
      booktitle = {NDSS 2015},
      organization = {Internet Society},
      day = {8},
      month = {February},
      year = {2015},
      abstract = {We propose Bloom cookies that encode a user's
                profile in a compact and privacy-preserving way,
                without preventing online services from using it
                for personalization purposes. The Bloom cookies
                design is inspired by our analysis of a large set
                of web search logs that shows drawbacks of two
                profile obfuscation techniques, namely profile
                generalization and noise injection, today used by
                many privacy-preserving personalization systems.
                We find that profile generalization significantly
                hurts personalization and fails to protect users
                from a server linking user sessions over time.
                Noise injection can address these problems, but
                only at the cost of a high communication overhead
                and a noise dictionary generated by a trusted
                third party. In contrast, Bloom cookies leverage
                Bloom filters as a privacy-preserving data
                structure to provide a more convenient privacy,
                personalization, and network efficiency tradeoff:
                they provide similar (or better) personalization
                and privacy than noise injection (and profile
                generalization), but with an order of magnitude
                lower communication cost and no noise dictionary.
                We discuss how Bloom cookies can be used for
                personalized web search, present an algorithm to
                automatically configure the noise in Bloom cookies
                given a user's privacy and personalization goals,
                and evaluate their performance compared to the
                state-of-the-art.},
      URL = {http://terraswarm.org/pubs/461.html}
  }
  

Posted by Barb Hoversten on 12 Nov 2014.
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