An efficient secure Internet of things data storage auditing protocol with adjustable parameter in cloud computing

被引:2
作者
Liu, Meng [1 ,2 ]
Wang, Xuan [1 ]
Yang, Chi [3 ]
Jiang, Zoe Lin [1 ]
Li, Ye [1 ]
机构
[1] Harbin Inst Technol, Shenzhen Grad Sch, Comp Applicat Res Ctr, Shenzhen 518055, Peoples R China
[2] Shandong Univ, Sch Mech Elect & Informat Engn, Weihai, Peoples R China
[3] CSIRO, Canberra, ACT, Australia
来源
INTERNATIONAL JOURNAL OF DISTRIBUTED SENSOR NETWORKS | 2017年 / 13卷 / 01期
基金
中国国家自然科学基金; 国家高技术研究发展计划(863计划);
关键词
Internet of things data; cloud storage; integrity auditing; third-party auditing; pairing-based cryptography; INTEGRITY VERIFICATION; BIG DATA;
D O I
10.1177/1550147716686579
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Nowadays, an increasing number of cloud users including both individuals and enterprises store their Internet of things data in cloud for benefits like cost saving. However, the cloud storage service is often regarded to be untrusted due to their loss of direct control over the data. Hence, it is necessary to verify the integrity of their data on cloud storage servers via a third party. In real cloud systems, it is very important to improve the performance of the auditing protocol. Hence, the well-designed and cost-effective auditing protocol is expected to meet with the performance requirement while the data size is very large in real cloud systems. In this article, we also propose an auditing protocol based on pairing-based cryptography, which can reduce the computation cost compared to the state-of-the-art third-party auditing protocol. Moreover, we also study how to determine the number of sectors to achieve the optimal performance of our auditing protocol in a case of the same challenged data. And an equation for computing the optimal number of sectors is proposed to further improve the performance of our auditing protocol. Both the mathematical analysis method and experiment results show that our solution is more efficient.
引用
收藏
页数:11
相关论文
共 24 条
[11]   External integrity verification for outsourced big data in cloud and IoT: A big picture [J].
Liu, Chang ;
Yang, Chi ;
Zhang, Xuyun ;
Chen, Jinjun .
FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE, 2015, 49 :58-67
[12]   Authorized Public Auditing of Dynamic Big Data Storage on Cloud with Efficient Verifiable Fine-Grained Updates [J].
Liu, Chang ;
Chen, Jinjun ;
Yang, Laurence T. ;
Zhang, Xuyun ;
Yang, Chi ;
Ranjan, Rajiv ;
Kotagiri, Ramamohanarao .
IEEE TRANSACTIONS ON PARALLEL AND DISTRIBUTED SYSTEMS, 2014, 25 (09) :2234-2244
[13]  
Nan XF, 2010, IEEE INT C BIOINFORM, P520, DOI 10.1109/BIBM.2010.5706621
[14]  
Shin S., 2015, J INTERNET SERV INFO, V5, P37
[15]   Remote Data Auditing in Cloud Computing Environments: A Survey, Taxonomy, and Open Issues [J].
Sookhak, Mehdi ;
Gani, Abdullah ;
Talebian, Hamid ;
Akhunzada, Adnan ;
Khan, Samee U. ;
Buyya, Rajkumar ;
Zomaya, Albert Y. .
ACM COMPUTING SURVEYS, 2015, 47 (04)
[16]   A review on remote data auditing in single cloud server: Taxonomy and open issues [J].
Sookhak, Mehdi ;
Talebian, Hamid ;
Ahmed, Ejaz ;
Gani, Abdullah ;
Khan, Muhammad Khurram .
JOURNAL OF NETWORK AND COMPUTER APPLICATIONS, 2014, 43 :121-141
[17]   Toward Publicly Auditable Secure Cloud Data Storage Services [J].
Wang, Cong ;
Ren, Kui ;
Lou, Wenjing ;
Li, Jin .
IEEE NETWORK, 2010, 24 (04) :19-24
[18]   Enabling Public Auditability and Data Dynamics for Storage Security in Cloud Computing [J].
Wang, Qian ;
Wang, Cong ;
Ren, Kui ;
Lou, Wenjing ;
Li, Jin .
IEEE TRANSACTIONS ON PARALLEL AND DISTRIBUTED SYSTEMS, 2011, 22 (05) :847-859
[19]  
Yamamoto G, 2007, P ECRYPT WORKSH SOFT, P21
[20]   A Time Efficient Approach for Detecting Errors in Big Sensor Data on Cloud [J].
Yang, Chi ;
Liu, Chang ;
Zhang, Xuyun ;
Nepal, Surya ;
Chen, Jinjun .
IEEE TRANSACTIONS ON PARALLEL AND DISTRIBUTED SYSTEMS, 2015, 26 (02) :329-339