P. M. Rao, Anusha Vangala, Saraswathi Pedada, Ashok Kumar Das, Athanasios V. Vasilakos
{"title":"Privacy-Preserving Lightweight Authentication for Location-Aware Edge-Enabled eHealth Systems","authors":"P. M. Rao, Anusha Vangala, Saraswathi Pedada, Ashok Kumar Das, Athanasios V. Vasilakos","doi":"10.1109/IOTM.001.2400008","DOIUrl":null,"url":null,"abstract":"With the rapid advancements in the Internet of Things (IoT), edge computing has a significant role in many eHealth applications. However, security and data privacy are major challenges due to the widespread popularity of the digital health domain. The network and data storage should withstand adversarial entities and allow access to only legitimate users. Medical users and servers must be registered with a trusted third-party authority to obtain permissions to authenticate remaining users. Millions of smart medical devices connect online to collect critical patient information, analyze reports, and perform meaningful decisions without human interaction. In this scenario, standard security is essential to safeguard eHealth applications. This research provides a secured, lightweight mobile edge computing framework to address these issues. The empirical results show that our framework mitigates computational overheads. The informal and formal analysis shows that our framework withstands potential attacks.","PeriodicalId":235472,"journal":{"name":"IEEE Internet of Things Magazine","volume":"17 6","pages":"76-82"},"PeriodicalIF":0.0000,"publicationDate":"2024-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Internet of Things Magazine","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IOTM.001.2400008","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
With the rapid advancements in the Internet of Things (IoT), edge computing has a significant role in many eHealth applications. However, security and data privacy are major challenges due to the widespread popularity of the digital health domain. The network and data storage should withstand adversarial entities and allow access to only legitimate users. Medical users and servers must be registered with a trusted third-party authority to obtain permissions to authenticate remaining users. Millions of smart medical devices connect online to collect critical patient information, analyze reports, and perform meaningful decisions without human interaction. In this scenario, standard security is essential to safeguard eHealth applications. This research provides a secured, lightweight mobile edge computing framework to address these issues. The empirical results show that our framework mitigates computational overheads. The informal and formal analysis shows that our framework withstands potential attacks.