The sharing of pathological data is highly important in various applications,such as remote diagnosis,graded diagnosis,illness treatment,and specialist system development.However,ensuring reliable,secure,privacy-prese...The sharing of pathological data is highly important in various applications,such as remote diagnosis,graded diagnosis,illness treatment,and specialist system development.However,ensuring reliable,secure,privacy-preserving,and efficient sharing of pathological data poses significant challenges.This paper presents a novel solution that leverages blockchain technology to ensure reliability in pathological data sharing.Additionally,it employs conditional proxy re-encryption(C-PRE)and public key encryption with equality test technology to control the scope and preserve the privacy of shared data.To assess the practicality of our solution,we implemented a prototype system using Hyperledger Fabric and conducted evaluations with various metrics.We also compared the solution with relevant schemes.The results demonstrate that the proposed solution effectively meets the requirements for pathological data sharing and is practical in production scenarios.展开更多
基金supported by National Natural Science Foundation of China under Grant 61972438Wuhu Science and Tech-nology Plan Project under Grant 2022yf50Key Research and Develop-ment Projects in Anhui Province under Grant 202004a05020002 and 2022a05020049.
文摘The sharing of pathological data is highly important in various applications,such as remote diagnosis,graded diagnosis,illness treatment,and specialist system development.However,ensuring reliable,secure,privacy-preserving,and efficient sharing of pathological data poses significant challenges.This paper presents a novel solution that leverages blockchain technology to ensure reliability in pathological data sharing.Additionally,it employs conditional proxy re-encryption(C-PRE)and public key encryption with equality test technology to control the scope and preserve the privacy of shared data.To assess the practicality of our solution,we implemented a prototype system using Hyperledger Fabric and conducted evaluations with various metrics.We also compared the solution with relevant schemes.The results demonstrate that the proposed solution effectively meets the requirements for pathological data sharing and is practical in production scenarios.
