Towards Privacy-Aware and Trustworthy Data Sharing Using Blockchain for Edge Intelligence

作     者：Youyang Qu Lichuan Ma Wenjie Ye Xuemeng Zhai Shui Yu Yunfeng Li David Smith 

作者机构：with Data61Commonwealth Scientific and Industrial Research Organization(CSIRO)Sydney 2015Australia School of Cyber EngineeringXidian UniversityXi’an 710126China the College of Engineering and ScienceVictoria UniversityMelbourne 3000Australia School of Information and Communication EngineeringUniversity of Electronic Science and Technology of ChinaChengdu 610054China School of Computer ScienceUniversity of Technology SydneySydney 2007Australia CNPIEC KEXIN LTD.Beijing 100020China. 

出 版 物：《Big Data Mining and Analytics》 (大数据挖掘与分析（英文）)

年 卷 期：2023年第6卷第4期

页      面：443-464页

核心收录：

学科分类：12[管理学] 02[经济学] 0202[经济学-应用经济学] 1201[管理学-管理科学与工程(可授管理学、工学学位)] 020204[经济学-金融学（含∶保险学）] 081104[工学-模式识别与智能系统] 08[工学] 0835[工学-软件工程] 0811[工学-控制科学与工程] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

基　　金：supported by the National Key Research and Development Program of China(No.2021YFF0900400) 

主　　题：edge intelligence blockchain personalized privacy preservation differential privacy Smart Healthcare Networks(SHNs) 

摘      要：The popularization of intelligent healthcare devices and big data analytics significantly boosts the development of Smart Healthcare Networks(SHNs).To enhance the precision of diagnosis,different participants in SHNs share health data that contain sensitive ***,the data exchange process raises privacy concerns,especially when the integration of health data from multiple sources(linkage attack)results in further *** attack is a type of dominant attack in the privacy domain,which can leverage various data sources for private data ***,adversaries launch poisoning attacks to falsify the health data,which leads to misdiagnosing or even physical *** protect private health data,we propose a personalized differential privacy model based on the trust levels among *** trust is evaluated by a defined community density,while the corresponding privacy protection level is mapped to controllable randomized noise constrained by differential *** avoid linkage attacks in personalized differential privacy,we design a noise correlation decoupling mechanism using a Markov stochastic *** addition,we build the community model on a blockchain,which can mitigate the risk of poisoning attacks during differentially private data transmission over *** experiments and analysis on real-world datasets have testified the proposed model,and achieved better performance compared with existing research from perspectives of privacy protection and effectiveness.