{"title":"Utility-Aware Data Anonymization Model for Healthcare Information","authors":"Fadi Alhaddadin, Jairo Gutiérrez","doi":"10.1109/SmartWorld-UIC-ATC-ScalCom-DigitalTwin-PriComp-Metaverse56740.2022.00372","DOIUrl":null,"url":null,"abstract":"The use of collected data is a valuable source for analysis that benefits both medical research and practice. Information privacy is considered a significant challenge that hinders using such information for research purposes. In terms of research, releasing patients’ information for research purposes may lead to privacy breaches for patients in various cases. Individual patients may not wish to be identifiable when using information about their health for research. This work proposes a utility-aware data anonymization model for sharing patients’ health information for research purposes in a privacy-preserving manner. The proposed model is interactive and involves a number of operations that are performed on patients’ information before releasing it for research purposes according to certain requirements specified by the data user (researcher).","PeriodicalId":43791,"journal":{"name":"Scalable Computing-Practice and Experience","volume":null,"pages":null},"PeriodicalIF":0.9000,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Scalable Computing-Practice and Experience","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SmartWorld-UIC-ATC-ScalCom-DigitalTwin-PriComp-Metaverse56740.2022.00372","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"COMPUTER SCIENCE, SOFTWARE ENGINEERING","Score":null,"Total":0}
引用次数: 0
Abstract
The use of collected data is a valuable source for analysis that benefits both medical research and practice. Information privacy is considered a significant challenge that hinders using such information for research purposes. In terms of research, releasing patients’ information for research purposes may lead to privacy breaches for patients in various cases. Individual patients may not wish to be identifiable when using information about their health for research. This work proposes a utility-aware data anonymization model for sharing patients’ health information for research purposes in a privacy-preserving manner. The proposed model is interactive and involves a number of operations that are performed on patients’ information before releasing it for research purposes according to certain requirements specified by the data user (researcher).
期刊介绍:
The area of scalable computing has matured and reached a point where new issues and trends require a professional forum. SCPE will provide this avenue by publishing original refereed papers that address the present as well as the future of parallel and distributed computing. The journal will focus on algorithm development, implementation and execution on real-world parallel architectures, and application of parallel and distributed computing to the solution of real-life problems.