Abstract
We propose a method for search privacy on the Internet, focusing on enhancing plausible deniability against search engine query-logs. The method approximates the target search results, without submitting the intended query and avoiding other exposing queries, by employing sets of queries representing more general concepts. We model the problem theoretically, and investigate the practical feasibility and effectiveness of the proposed solution with a set of real queries with privacy issues on a large web collection. The findings may have implications for other IR research areas, such as query expansion and fusion in meta-search.
Keywords
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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 subscriptionsPreview
Unable to display preview. Download preview PDF.
References
Barbaro, M., Zeller, T.: A Face Is Exposed for AOL Searcher No. 4417749 (2006), http://www.nytimes.com/2006/08/09/technology/09aol.html (accessed June 2010)
Boldi, P., Bonchi, F., Castillo, C., Vigna, S.: From ”Dango” to ”Japanese Cakes”: Query reformulation models and patterns. In: WI-IAT, pp. 183–190. IEEE Computer Society, Los Alamitos (2009)
Domingo-Ferrer, J., Solanas, A., Castella-Roca, J.: h(k)-private information retrieval from privacy-uncooperative queryable databases. Online Inf. Review 33(4), 720–744 (2009)
Fagin, R., Kumar, R., Sivakumar, D.: Comparing top k lists. SIAM J. Discrete Math. 17(1), 134–160 (2003)
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, ch. 23, pp. 417–436. Oxford University Press, Oxford (2009)
Jones, R., Kumar, R., Pang, B., Tomkins, A.: Vanity fair: privacy in querylog bundles. In: CIKM, pp. 853–862. ACM, New York (2008)
Kumar, R., Novak, J., Pang, B., Tomkins, A.: On anonymizing query logs via token-based hashing. In: WWW, pp. 629–638. ACM, New York (2007)
Murugesan, M., Clifton, C.: Providing privacy through plausibly deniable search. In: SDM, pp. 768–779. SIAM, Philadelphia (2009)
Ostrovsky, R., Skeith, W.I.: A survey of single-database PIR: techniques and applications. In: Okamoto, T., Wang, X. (eds.) PKC 2007. LNCS, vol. 4450, pp. 393–411. Springer, Heidelberg (2007)
Pang, H., Ding, X., Xiao, X.: Embellishing text search queries to protect user privacy. In: VLDB (2010)
Pass, G., Chowdhury, A., Torgeson, C.: A picture of search. In: InfoScale. ACM, New York (2006)
Saint-Jean, F., Johnson, A., Boneh, D., Feigenbaum, J.: Private web search. In: WPES, pp. 84–90. ACM, New York (2007)
Shen, X., Tan, B., Zhai, C.: Privacy protection in personalized search. SIGIR Forum 41(1), 4–17 (2007)
Strube, M., Ponzetto, S.P.: Wikirelate! computing semantic relatedness using wikipedia. In: AAAI, pp. 1419–1424. AAAI Press, Menlo Park (2006)
Varelas, G., Voutsakis, E., Raftopoulou, P., Petrakis, E., Milios, E.: Semantic similarity methods in wordnet and their application to information retrieval on the web. In: WIDM, p. 16. ACM, New York (2005)
Wu, Z., Palmer, M.: Verb semantics and lexical selection. In: Proc. of the 32nd Ann. Meeting of the Assoc. for Computational Linguistics, Las Cruces, New Mexico, pp. 133–138 (1994)
Yan, P., Jiao, Y., Hurson, A., Potok, T.: Semantic-based information retrieval of biomedical data. In: SAC, p. 1704. ACM, New York (2006)
Yekhanin, S.: Private information retrieval. Commun. ACM 53(4), 68–73 (2010)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2011 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Arampatzis, A., Efraimidis, P., Drosatos, G. (2011). Enhancing Deniability against Query-Logs. In: Clough, P., et al. Advances in Information Retrieval. ECIR 2011. Lecture Notes in Computer Science, vol 6611. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-20161-5_13
Download citation
DOI: https://doi.org/10.1007/978-3-642-20161-5_13
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-20160-8
Online ISBN: 978-3-642-20161-5
eBook Packages: Computer ScienceComputer Science (R0)