{"title":"PAAS: A Privacy-Preserving Attribute-Based Authentication System for eHealth Networks","authors":"Linke Guo, Chi Zhang, Jinyuan Sun, Yuguang Fang","doi":"10.1109/ICDCS.2012.45","DOIUrl":null,"url":null,"abstract":"Recently, eHealth systems have replaced paper based medical system due to its prominent features of convenience and accuracy. Also, since the medical data can be stored on any kind of digital devices, people can easily obtain medical services at any time and any place. However, privacy concern over patient medical data draws an increasing attention. In the current eHealth networks, patients are assigned multiple attributes which directly reflect their symptoms, undergoing treatments, etc. Those life-threatened attributes need to be verified by an authorized medical facilities, such as hospitals and clinics. When there is a need for medical services, patients have to be authenticated by showing their identities and the corresponding attributes in order to take appropriate healthcare actions. However, directly disclosing those attributes for verification may expose real identities. Therefore, existing eHealth systems fail to preserve patients' private attribute information while maintaining original functionalities of medical services. To solve this dilemma, we propose a framework called PAAS which leverages users' verifiable attributes to authenticate users in eHealth systems while preserving their privacy issues. In our system, instead of letting centralized infrastructures take care of authentication, our scheme only involves two end users. We also offer authentication strategies with progressive privacy requirements among patients or between patients and physicians. Based on the security and efficiency analysis, we show our framework is better than existing eHealth systems in terms of privacy preservation and practicality.","PeriodicalId":6300,"journal":{"name":"2012 IEEE 32nd International Conference on Distributed Computing Systems","volume":"62 1","pages":"224-233"},"PeriodicalIF":0.0000,"publicationDate":"2012-06-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"111","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2012 IEEE 32nd International Conference on Distributed Computing Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICDCS.2012.45","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 111
Abstract
Recently, eHealth systems have replaced paper based medical system due to its prominent features of convenience and accuracy. Also, since the medical data can be stored on any kind of digital devices, people can easily obtain medical services at any time and any place. However, privacy concern over patient medical data draws an increasing attention. In the current eHealth networks, patients are assigned multiple attributes which directly reflect their symptoms, undergoing treatments, etc. Those life-threatened attributes need to be verified by an authorized medical facilities, such as hospitals and clinics. When there is a need for medical services, patients have to be authenticated by showing their identities and the corresponding attributes in order to take appropriate healthcare actions. However, directly disclosing those attributes for verification may expose real identities. Therefore, existing eHealth systems fail to preserve patients' private attribute information while maintaining original functionalities of medical services. To solve this dilemma, we propose a framework called PAAS which leverages users' verifiable attributes to authenticate users in eHealth systems while preserving their privacy issues. In our system, instead of letting centralized infrastructures take care of authentication, our scheme only involves two end users. We also offer authentication strategies with progressive privacy requirements among patients or between patients and physicians. Based on the security and efficiency analysis, we show our framework is better than existing eHealth systems in terms of privacy preservation and practicality.