Privacy exposure measure: a privacy-preserving technique for health-related web search

Rafiullah Khan, Muhammad Arshad Islam, Mohib Ullah, Muhammad Aleem, Muhammad Azhar Iqbal

Research output: Contribution to journalArticlepeer-review


The increasing use of web search engines (WSEs) for searching healthcare information has resulted in a growing number of users posting personal health information online. A recent survey demonstrates that over 80% of patients use WSE to seek health information. However, WSE stores these user's queries to analyze user behavior, result ranking, personalization, targeted advertisements, and other activities. Since health-related queries contain privacy-sensitive information that may infringe user's privacy. Therefore, privacy-preserving web search techniques such as anonymizing networks, profile obfuscation, private information retrieval (PIR) protocols etc. are used to ensure the user's privacy. In this paper, we propose Privacy Exposure Measure (PEM), a technique that facilitates user to control his/her privacy exposure while using the PIR protocols. PEM assesses the similarity between the user's profile and query before posting to WSE and assists the user in avoiding privacy exposure. The experiments demonstrate 37.2% difference between users' profile created through PEM-powered-PIR protocol and other usual users' profile. Moreover, PEM offers more privacy to the user even in case of machine-learning attack.
Original languageEnglish
Pages (from-to)1196-1204
Number of pages9
JournalJournal of Medical Imaging and Health Informatics
Issue number6
Publication statusPublished - Aug 2019
Externally publishedYes


  • Web Search Privacy
  • Health Privacy
  • Privacy Estimation Measure


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