Global and Personalized Query Probability for Obfuscation-Based Web Search

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Scopus citations

Abstract

Over the past few years, the volumes of digital information have increased dramatically. Web search engines become indispensable to our daily lives due to their capability of filtering relevant information. The web search engines collect users' online behavior data which implies their personalized interest, even contains sensitive information. A malicious attacker may benefit from advertising or manipulating political campaigns, which poses a serious threat to public security. In this paper, we propose two new methods to generate dummy queries base on global and personalized queries' probability. The generated anonymous queries set has greater information entropy which helps to protect user's intent in web search. Experiment results verify the validity of our methods.

Original languageEnglish
Title of host publicationProceedings - 11th IEEE International Conference on Knowledge Graph, ICKG 2020
EditorsEnhong Chen, Grigoris Antoniou, Xindong Wu, Vipin Kumar
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages259-266
Number of pages8
ISBN (Electronic)9781728181561
DOIs
StatePublished - Aug 2020
Event11th IEEE International Conference on Knowledge Graph, ICKG 2020 - Virtual, Online, China
Duration: 9 Aug 202011 Aug 2020

Publication series

NameProceedings - 11th IEEE International Conference on Knowledge Graph, ICKG 2020

Conference

Conference11th IEEE International Conference on Knowledge Graph, ICKG 2020
Country/TerritoryChina
CityVirtual, Online
Period9/08/2011/08/20

Keywords

  • Global query probability
  • Kernel Density Estimation
  • Personalized query probability

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