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Blockchain-Based Mobile Crowd Sensing in Industrial Systems
Huang, Junqin1; Kong LH(孔令和)1; Dai, Hong-Ning2; Ding, Weiping3; Cheng, Long4; Chen GH(陈贵海)1; Jin X(金曦)5; Zeng P(曾鹏)5
Department工业控制网络与系统研究室
Source PublicationIEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
ISSN1551-3203
2020
Volume16Issue:10Pages:6553-6563
Indexed BySCI ; EI
EI Accession number20202908940747
WOS IDWOS:000545243500032
Contribution Rank5
Funding OrganizationNational Natural Science Foundation of ChinaNational Natural Science Foundation of China [61972253, 61672349, U190820096, 61672353, 61672348, 61976120] ; Program for Professor of Special Appointment (Eastern Scholar) at Shanghai Institutions of Higher Learning ; Macao's key R&D Funding Program [0025/2019/AKP] ; Macao Science and Technology Development Fund [0026/2018/A1] ; Natural Science Foundation of Jiangsu ProvinceJiangsu Planned Projects for Postdoctoral Research FundsNatural Science Foundation of Jiangsu Province [BK20191445] ; Six Talent Peaks Project of Jiangsu Province [XYDXXJS-048] ; Qing Lan Project of Jiangsu Province
KeywordSensors Blockchain Reliability Data integrity Mobile handsets Industries Blockchain mobile crowd sensing (MCS) mobility scalability security smart factory
Abstract

The smart factory is a representative element reshaping conventional computer-aided industry to data-driven smart industry, while it is nontrivial to achieve cost effectiveness, reliability, mobility, and scalability of smart industrial systems. Data-driven industrial systems mainly rely on sensory data collected from statically deployed sensors. However, the spatial coverage of industrial sensor networks is constrained due to the high deployment and maintenance cost. Recently, mobile crowd sensing (MCS) has become a new sensing paradigm owing to its merits, such as cost effectiveness, mobility, and scalability. Nevertheless, traditional MCS systems are vulnerable to malicious attacks and single point of failure due to the centralized architecture. To this end, in this article we integrate MCS with industrial systems without introducing any additional dedicated devices. To overcome the drawbacks of traditional MCS systems, we propose a blockchain-based MCS system (BMCS). In particular, we exploit miners to verify the sensory data and design a dynamic reward ranking incentive mechanism to mitigate the imbalance of multiple sensing tasks. Meanwhile, we also develop a sensory data quality detection scheme to identify and mitigate the data anomaly. We implement a prototype of the BMCS on top of Ethereum and conduct extensive experiments on a realistic factory workroom. Both experimental results and security analysis demonstrate that the BMCS can secure industrial systems and improve the system reliability.

Language英语
WOS SubjectAutomation & Control Systems ; Computer Science, Interdisciplinary Applications ; Engineering, Industrial
WOS KeywordSECURITY ; INTERNET ; PRIVACY
WOS Research AreaAutomation & Control Systems ; Computer Science ; Engineering
Funding ProjectNational Natural Science Foundation of China[61972253] ; National Natural Science Foundation of China[61672349] ; National Natural Science Foundation of China[U190820096] ; National Natural Science Foundation of China[61672353] ; National Natural Science Foundation of China[61672348] ; National Natural Science Foundation of China[61976120] ; Program for Professor of Special Appointment (Eastern Scholar) at Shanghai Institutions of Higher Learning ; Macao's key R&D Funding Program[0025/2019/AKP] ; Macao Science and Technology Development Fund[0026/2018/A1] ; Natural Science Foundation of Jiangsu Province[BK20191445] ; Six Talent Peaks Project of Jiangsu Province[XYDXXJS-048] ; Qing Lan Project of Jiangsu Province
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Cited Times:3[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttp://ir.sia.cn/handle/173321/27335
Collection工业控制网络与系统研究室
Corresponding AuthorKong LH(孔令和)
Affiliation1.Shanghai Jiao Tong University, Shanghai 200240, China
2.Macau University of Science and Technology, Taipa, Macau
3.School of Information Science and Technology, Nantong University, Nantong 226019, China
4.School of Computing, Clemson University, Clemson, SC 29634 USA
5.Laboratory of Networked Control Systems, Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang 110016, China
Recommended Citation
GB/T 7714
Huang, Junqin,Kong LH,Dai, Hong-Ning,et al. Blockchain-Based Mobile Crowd Sensing in Industrial Systems[J]. IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS,2020,16(10):6553-6563.
APA Huang, Junqin.,Kong LH.,Dai, Hong-Ning.,Ding, Weiping.,Cheng, Long.,...&Zeng P.(2020).Blockchain-Based Mobile Crowd Sensing in Industrial Systems.IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS,16(10),6553-6563.
MLA Huang, Junqin,et al."Blockchain-Based Mobile Crowd Sensing in Industrial Systems".IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS 16.10(2020):6553-6563.
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