title: Privacy-preserving self-helped medical diagnosis scheme based on secure two-party computation in wireless sensor networks.
abstract: With the continuing growth of wireless sensor networks in pervasive medical care, people pay more and more attention to privacy in medical monitoring, diagnosis, treatment, and patient care. On one hand, we expect the public health institutions to provide us with better service. On the other hand, we would not like to leak our personal health information to them. In order to balance this contradiction, in this paper we design a privacy-preserving self-helped medical diagnosis scheme based on secure two-party computation in wireless sensor networks so that patients can privately diagnose themselves by inputting a health card into a self-helped medical diagnosis ATM to obtain a diagnostic report just like drawing money from a bank ATM without revealing patients' health information and doctors' diagnostic skill. It makes secure self-helped disease diagnosis feasible and greatly benefits patients as well as relieving the heavy pressure of public health institutions.
authors.affiliation: State Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications, Beijing 100876, China.
authors.forename: Yi
authors.identifier: 0000-0002-1427-8682
authors.initials: Y
authors.lastname: Sun
authors.affiliation: State Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications, Beijing 100876, China.
authors.forename: Qiaoyan
authors.initials: Q
authors.lastname: Wen
authors.affiliation: Brain Image Processing, Columbia University, New York, NY 10032, USA.
authors.forename: Yudong
authors.initials: Y
authors.lastname: Zhang
authors.affiliation: State Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications, Beijing 100876, China.
authors.forename: Wenmin
authors.initials: W
authors.lastname: Li
mesh_terms: D000465:Algorithms; D003195:Computer Communication Networks; D016494:Computer Security; D003199:Computer Systems; D003219:Confidentiality; D003936:Diagnosis, Computer-Assisted / Q000379:methods*; D006801:Humans; D008490:Medical Informatics / Q000458:organization & administration; D010358:Patient Participation; D018802:Patient-Centered Care; D018907:Privacy; D011336:Probability; D012648:Self Care; D014584:User-Computer Interface