{"doi":"10.3390/s21144933","volume":21,"publisher":"MDPI AG","issue":"14","author":[{"last_name":"Attaullah","full_name":"Attaullah, Hasina","id":"254998","first_name":"Hasina","orcid":"0000-0002-6902-6116"},{"last_name":"Anjum","full_name":"Anjum, Adeel","first_name":"Adeel"},{"full_name":"Kanwal, Tehsin","last_name":"Kanwal","first_name":"Tehsin"},{"last_name":"Malik","full_name":"Malik, Saif Ur Rehman","first_name":"Saif Ur Rehman"},{"full_name":"Asheralieva, Alia","last_name":"Asheralieva","first_name":"Alia"},{"first_name":"Hassan","full_name":"Malik, Hassan","last_name":"Malik"},{"full_name":"Zoha, Ahmed","last_name":"Zoha","first_name":"Ahmed"},{"last_name":"Arshad","full_name":"Arshad, Kamran","first_name":"Kamran"},{"first_name":"Muhammad Ali","last_name":"Imran","full_name":"Imran, Muhammad Ali"}],"alternative_id":["4810"],"date_updated":"2024-07-18T11:34:23Z","article_number":"4933","language":[{"iso":"eng"}],"intvolume":"        21","type":"journal_article","publication_identifier":{"eissn":["1424-8220"]},"abstract":[{"lang":"eng","text":"                  With the advent of smart health, smart cities, and smart grids, the amount of data has grown swiftly. When the collected data is published for valuable information mining, privacy turns out to be a key matter due to the presence of sensitive information. Such sensitive information comprises either a single sensitive attribute (an individual has only one sensitive attribute) or multiple sensitive attributes (an individual can have multiple sensitive attributes). Anonymization of data sets with multiple sensitive attributes presents some unique problems due to the correlation among these attributes. Artificial intelligence techniques can help the data publishers in anonymizing such data. To the best of our knowledge, no fuzzy logic-based privacy model has been proposed until now for privacy preservation of multiple sensitive attributes. In this paper, we propose a novel privacy preserving model F-Classify that uses fuzzy logic for the classification of quasi-identifier and multiple sensitive attributes. Classes are defined based on defined rules, and every tuple is assigned to its class according to attribute value. The working of the F-Classify Algorithm is also verified using HLPN. A wide range of experiments on healthcare data sets acknowledged that F-Classify surpasses its counterparts in terms of privacy and utility. Being based on artificial intelligence, it has a lower execution time than other approaches.\r\n                "}],"tmp":{"short":"CC BY (4.0)","image":"/images/cc_by.png","name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode"},"publication_status":"published","year":"2021","_id":"4803","status":"public","publication":"Sensors","title":"F-Classify: Fuzzy Rule Based Classification Method for Privacy Preservation of Multiple Sensitive Attributes","date_created":"2024-07-10T14:44:51Z","user_id":"220548","citation":{"bibtex":"@article{Attaullah_Anjum_Kanwal_Malik_Asheralieva_Malik_Zoha_Arshad_Imran_2021, title={F-Classify: Fuzzy Rule Based Classification Method for Privacy Preservation of Multiple Sensitive Attributes}, volume={21}, DOI={<a href=\"https://doi.org/10.3390/s21144933\">10.3390/s21144933</a>}, number={144933}, journal={Sensors}, publisher={MDPI AG}, author={Attaullah, Hasina and Anjum, Adeel and Kanwal, Tehsin and Malik, Saif Ur Rehman and Asheralieva, Alia and Malik, Hassan and Zoha, Ahmed and Arshad, Kamran and Imran, Muhammad Ali}, year={2021} }","mla":"Attaullah, Hasina, et al. “F-Classify: Fuzzy Rule Based Classification Method for Privacy Preservation of Multiple Sensitive Attributes.” <i>Sensors</i>, vol. 21, no. 14, 4933, MDPI AG, 2021, doi:<a href=\"https://doi.org/10.3390/s21144933\">10.3390/s21144933</a>.","ama":"Attaullah H, Anjum A, Kanwal T, et al. F-Classify: Fuzzy Rule Based Classification Method for Privacy Preservation of Multiple Sensitive Attributes. <i>Sensors</i>. 2021;21(14). doi:<a href=\"https://doi.org/10.3390/s21144933\">10.3390/s21144933</a>","ieee":"H. Attaullah <i>et al.</i>, “F-Classify: Fuzzy Rule Based Classification Method for Privacy Preservation of Multiple Sensitive Attributes,” <i>Sensors</i>, vol. 21, no. 14, 2021.","chicago":"Attaullah, Hasina, Adeel Anjum, Tehsin Kanwal, Saif Ur Rehman Malik, Alia Asheralieva, Hassan Malik, Ahmed Zoha, Kamran Arshad, and Muhammad Ali Imran. “F-Classify: Fuzzy Rule Based Classification Method for Privacy Preservation of Multiple Sensitive Attributes.” <i>Sensors</i> 21, no. 14 (2021). <a href=\"https://doi.org/10.3390/s21144933\">https://doi.org/10.3390/s21144933</a>.","apa":"Attaullah, H., Anjum, A., Kanwal, T., Malik, S. U. R., Asheralieva, A., Malik, H., … Imran, M. A. (2021). F-Classify: Fuzzy Rule Based Classification Method for Privacy Preservation of Multiple Sensitive Attributes. <i>Sensors</i>, <i>21</i>(14). <a href=\"https://doi.org/10.3390/s21144933\">https://doi.org/10.3390/s21144933</a>","short":"H. Attaullah, A. Anjum, T. Kanwal, S.U.R. Malik, A. Asheralieva, H. Malik, A. Zoha, K. Arshad, M.A. Imran, Sensors 21 (2021).","alphadin":"<span style=\"font-variant:small-caps;\"><span style=\"font-variant:small-caps;\">Attaullah, Hasina</span> ; <span style=\"font-variant:small-caps;\">Anjum, Adeel</span> ; <span style=\"font-variant:small-caps;\">Kanwal, Tehsin</span> ; <span style=\"font-variant:small-caps;\">Malik, Saif Ur Rehman</span> ; <span style=\"font-variant:small-caps;\">Asheralieva, Alia</span> ; <span style=\"font-variant:small-caps;\">Malik, Hassan</span> ; <span style=\"font-variant:small-caps;\">Zoha, Ahmed</span> ; <span style=\"font-variant:small-caps;\">Arshad, Kamran</span> ; u. a.</span>: F-Classify: Fuzzy Rule Based Classification Method for Privacy Preservation of Multiple Sensitive Attributes. In: <i>Sensors</i> Bd. 21, MDPI AG (2021), Nr. 14"}}