{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,9,28]],"date-time":"2025-09-28T20:49:34Z","timestamp":1759092574830,"version":"3.37.3"},"reference-count":29,"publisher":"Wiley","license":[{"start":{"date-parts":[[2020,7,14]],"date-time":"2020-07-14T00:00:00Z","timestamp":1594684800000},"content-version":"unspecified","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100004054","name":"King Abdulaziz University","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100004054","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Scientific Programming"],"published-print":{"date-parts":[[2020,7,14]]},"abstract":"<jats:p>With the advancement in ICT, web search engines have become a preferred source to find health-related information published over the Internet. Google alone receives more than one billion health-related queries on a daily basis. However, in order to provide the results most relevant to the user, WSEs maintain the users\u2019 profiles. These profiles may contain private and sensitive information such as the user\u2019s health condition, disease status, and others. Health-related queries contain privacy-sensitive information that may infringe user\u2019s privacy, as the identity of a user is exposed and may be misused by the WSE and third parties. This raises serious concerns since the identity of a user is exposed and may be misused by third parties. One well-known solution to preserve privacy involves issuing the queries via peer-to-peer private information retrieval protocol, such as useless user profile (UUP), thereby hiding the user\u2019s identity from the WSE. This paper investigates the level of protection offered by UUP. For this purpose, we present QuPiD (query profile distance) attack: a machine learning-based attack that evaluates the effectiveness of UUP in privacy protection. QuPiD attack determines the distance between the user\u2019s profile (web search history) and upcoming query using our proposed novel feature vector. The experiments were conducted using ten classification algorithms belonging to the tree-based, rule-based, lazy learner, metaheuristic, and Bayesian families for the sake of comparison. Furthermore, two subsets of an America Online dataset (noisy and clean datasets) were used for experimentation. The results show that the proposed QuPiD attack associates more than 70% queries to the correct user with a precision of over 72% for the clean dataset, while for the noisy dataset, the proposed QuPiD attack associates more than 40% queries to the correct user with 70% precision.<\/jats:p>","DOI":"10.1155\/2020\/8868686","type":"journal-article","created":{"date-parts":[[2020,7,14]],"date-time":"2020-07-14T23:33:38Z","timestamp":1594769618000},"page":"1-11","source":"Crossref","is-referenced-by-count":13,"title":["QuPiD Attack: Machine Learning-Based Privacy Quantification Mechanism for PIR Protocols in Health-Related Web Search"],"prefix":"10.1155","volume":"2020","author":[{"given":"Rafiullah","family":"Khan","sequence":"first","affiliation":[{"name":"Institute of Computer Science and Information Technology, The University of Agriculture, Peshawar, Pakistan"},{"name":"Capital University of Science and Technology, Islamabad, Pakistan"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3576-8365","authenticated-orcid":true,"given":"Arshad","family":"Ahmad","sequence":"additional","affiliation":[{"name":"Department of Computer Science, University of Swabi, Anbar, Pakistan"}]},{"given":"Alhuseen Omar","family":"Alsayed","sequence":"additional","affiliation":[{"name":"Deanship of Scientific Research, King Abdulaziz University Jeddah, Jeddah, Saudi Arabia"}]},{"given":"Muhammad","family":"Binsawad","sequence":"additional","affiliation":[{"name":"Faculty of Computer Information Systems, King Abdulaziz University Jeddah, Jeddah, Saudi Arabia"}]},{"given":"Muhammad Arshad","family":"Islam","sequence":"additional","affiliation":[{"name":"National University of Computer and Emerging Sciences, Islamabad, Pakistan"}]},{"given":"Mohib","family":"Ullah","sequence":"additional","affiliation":[{"name":"Institute of Computer Science and Information Technology, The University of Agriculture, Peshawar, Pakistan"},{"name":"Capital University of Science and Technology, Islamabad, Pakistan"}]}],"member":"311","reference":[{"key":"1","doi-asserted-by":"publisher","DOI":"10.9738\/intsurg-d-17-00099.1"},{"first-page":"1","volume-title":"Health online 2013","year":"2013","key":"2"},{"key":"3","doi-asserted-by":"publisher","DOI":"10.1166\/jmihi.2019.2709"},{"key":"4","doi-asserted-by":"publisher","DOI":"10.1145\/3371390"},{"key":"5","doi-asserted-by":"publisher","DOI":"10.1287\/mnsc.2018.3255"},{"key":"6","doi-asserted-by":"publisher","DOI":"10.2139\/ssrn.3516104"},{"year":"2006","key":"8"},{"volume-title":"A picture of search. 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