标题:EVA: Efficient Versatile Auditing Scheme for IoT-Based Datamarket in Jointcloud
作者:Huang, Ke ;Zhang, Xiaosong ;Mu, Yi ;Rezaeibagha, Fatemeh ;Wang, Xiaofen ;Li, Jingwei ;Xia, Qi ;Qin, Jing
作者机构:[Huang, Ke ;Zhang, Xiaosong ;Wang, Xiaofen ;Li, Jingwei ;Xia, Qi ] Center for Cyber Security, College of Computer Science and Engineering, University 更多
通讯作者:Zhang, Xiaosong
通讯作者地址:[Zhang, X] Center for Cyber Security, College of Computer Science and Engineering, University of Electronic Science and Technology of ChinaChina;
来源:IEEE Internet of Things Journal
出版年:2020
卷:7
期:2
页码:882-892
DOI:10.1109/JIOT.2019.2945921
关键词:Auditing; data dynamic; jointcloud; security
摘要:Cloud storage offers convenient outsourcing services to users, and it serves as a basic platform to drive Internet-of-Things (IoT) where massive devices are connected to the cloud storage and interact with each other. However, cloud storage is more than a data warehouse. In the literature, data market was proposed as a novel model to empower IoT, where data are circulated as merchandise in the digital marketplace with financial activities. When storing IoT data in cloud storage, security and efficiency rules should be applied. Meanwhile, data dynamics is counted as a critical factor to the feasibility of datamarket as data are supposed to be manipulated through circulation and exploitation for IoT. Another issue is the single-point-of-failure (SPoF) of cloud server in which the initiative of jointcloud was suggested. Since providing data security, efficiency, and dynamics simultaneously is challenging, in this article, we propose a versatile auditing scheme (EVA) as a solution to problems. Our proposal ensures that data are securely, efficiently, and dynamically stored in the jointcloud meanwhile supported by data trades via blockchain. We give a comprehensive security analysis based on our security definitions and experiments to support our claims. The evidence has shown that our EVA is efficient for processing large files when proper parameters are chosen. © 2014 IEEE.
收录类别:EI;SCOPUS
资源类型:期刊论文
原文链接:https://www.scopus.com/inward/record.uri?eid=2-s2.0-85079773759&doi=10.1109%2fJIOT.2019.2945921&partnerID=40&md5=d59061844bf5cdda9ca969c20b4edbf4
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