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A Versatile Tool for Privacy-Enhanced Web Search

  • Avi Arampatzis
  • George Drosatos
  • Pavlos S. Efraimidis
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7814)

Abstract

We consider the problem of privacy leaks suffered by Internet users when they perform web searches, and propose a framework to mitigate them. Our approach, which builds upon and improves recent work on search privacy, approximates the target search results by replacing the private user query with a set of blurred or scrambled queries. The results of the scrambled queries are then used to cover the original user interest. We model the problem theoretically, define a set of privacy objectives with respect to web search and investigate the effectiveness of the proposed solution with a set of real queries on a large web collection. Experiments show great improvements in retrieval effectiveness over a previously reported baseline in the literature. Furthermore, the methods are more versatile, predictably-behaved, applicable to a wider range of information needs, and the privacy they provide is more comprehensible to the end-user.

Keywords

Document Sample Semantic Approach Retrieval Effectiveness Target Document Pointwise Mutual Information 
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.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Avi Arampatzis
    • 1
  • George Drosatos
    • 1
  • Pavlos S. Efraimidis
    • 1
  1. 1.Department of Electrical and Computer EngineeringDemocritus University of ThraceXanthiGreece

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