Md. Zakirul Alam Bhuiyan, Mdaliuz Zaman, Guojun Wang, Tian Wang, Jie Wu
{"title":"Privacy-Protected Data Collection in Wireless Medical Sensor Networks","authors":"Md. Zakirul Alam Bhuiyan, Mdaliuz Zaman, Guojun Wang, Tian Wang, Jie Wu","doi":"10.1109/NAS.2017.8026872","DOIUrl":null,"url":null,"abstract":"Medical data collection in healthcare monitoring applications through traditional frameworks raise serious concerns of patient data privacy and security, due to numerous security threats and attacks. In this paper, we investigate the concerns with privacy protected data collection and propose a novel patient privacy protected data collection framework with the aim to provide patient data privacy. We present a new secrete sharing scheme and a share reconstruction scheme for patient data privacy. We consider a distributed database consisting of multiple edge servers and each server receives a share of the patient data. Implementation result shows that secret share generation and sharing reconstruction do not require much computation time.","PeriodicalId":222161,"journal":{"name":"2017 International Conference on Networking, Architecture, and Storage (NAS)","volume":"86 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 International Conference on Networking, Architecture, and Storage (NAS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/NAS.2017.8026872","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 6
Abstract
Medical data collection in healthcare monitoring applications through traditional frameworks raise serious concerns of patient data privacy and security, due to numerous security threats and attacks. In this paper, we investigate the concerns with privacy protected data collection and propose a novel patient privacy protected data collection framework with the aim to provide patient data privacy. We present a new secrete sharing scheme and a share reconstruction scheme for patient data privacy. We consider a distributed database consisting of multiple edge servers and each server receives a share of the patient data. Implementation result shows that secret share generation and sharing reconstruction do not require much computation time.