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云辅助人体传感器网络多用户模型中具有隐私保护的公开审计

Public Auditing with Privacy Protection in a Multi-User Model of Cloud-Assisted Body Sensor Networks.

作者信息

Li Song, Cui Jie, Zhong Hong, Liu Lu

机构信息

School of Computer Science and Technology, Anhui University, Hefei 230601, China.

Department of Computing and Mathematics, University of Derby, Derby DE22 1GB, UK.

出版信息

Sensors (Basel). 2017 May 5;17(5):1032. doi: 10.3390/s17051032.

Abstract

Wireless Body Sensor Networks (WBSNs) are gaining importance in the era of the Internet of Things (IoT). The modern medical system is a particular area where the WBSN techniques are being increasingly adopted for various fundamental operations. Despite such increasing deployments of WBSNs, issues such as the infancy in the size, capabilities and limited data processing capacities of the sensor devices restrain their adoption in resource-demanding applications. Though providing computing and storage supplements from cloud servers can potentially enrich the capabilities of the WBSNs devices, data security is one of the prevailing issues that affects the reliability of cloud-assisted services. Sensitive applications such as modern medical systems demand assurance of the privacy of the users' medical records stored in distant cloud servers. Since it is economically impossible to set up private cloud servers for every client, auditing data security managed in the remote servers has necessarily become an integral requirement of WBSNs' applications relying on public cloud servers. To this end, this paper proposes a novel certificateless public auditing scheme with integrated privacy protection. The multi-user model in our scheme supports groups of users to store and share data, thus exhibiting the potential for WBSNs' deployments within community environments. Furthermore, our scheme enriches user experiences by offering public verifiability, forward security mechanisms and revocation of illegal group members. Experimental evaluations demonstrate the security effectiveness of our proposed scheme under the Random Oracle Model (ROM) by outperforming existing cloud-assisted WBSN models.

摘要

无线体域网(WBSNs)在物联网(IoT)时代正变得越来越重要。现代医疗系统是一个特别的领域,WBSN技术正越来越多地被应用于各种基础操作。尽管WBSNs的部署不断增加,但诸如传感器设备在尺寸、功能和数据处理能力方面尚不成熟等问题,限制了它们在资源需求较高的应用中的采用。虽然从云服务器提供计算和存储补充可能会丰富WBSNs设备的功能,但数据安全是影响云辅助服务可靠性的一个普遍问题。诸如现代医疗系统等敏感应用要求确保存储在远程云服务器中的用户病历的隐私性。由于为每个客户建立私有云服务器在经济上是不可能的,因此对远程服务器中管理的数据安全进行审计必然成为依赖公共云服务器的WBSNs应用的一项不可或缺的要求。为此,本文提出了一种具有集成隐私保护的新型无证书公共审计方案。我们方案中的多用户模型支持用户组存储和共享数据,从而展现了在社区环境中部署WBSNs的潜力。此外,我们的方案通过提供公共可验证性、前向安全机制和非法组成员撤销功能,丰富了用户体验。实验评估表明,在随机预言模型(ROM)下,我们提出的方案通过优于现有的云辅助WBSN模型,展现了其安全有效性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5602/5469637/d00abf1c0910/sensors-17-01032-g001.jpg

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