TY - JOUR
T1 - Blockchain-Based Mobile Crowd Sensing in Industrial Systems
AU - Huang, Junqin
AU - Kong, Linghe
AU - Dai, Hong Ning
AU - Ding, Weiping
AU - Cheng, Long
AU - Chen, Guihai
AU - Jin, Xi
AU - Zeng, Peng
N1 - Funding Information:
This work was supported in part by the National Natural Science Foundation of China under Grant 61972253, Grant 61672349, Grant U190820096, Grant 61672353, Grant 61672348, and Grant 61976120, in part by the Program for Professor of Special Appointment (Eastern Scholar) at Shanghai Institutions of Higher Learning, in part by the Macao’s key R&D Funding Program under Grant 0025/2019/AKP, in part by the Macao Science and Technology Development Fund under Grant 0026/2018/A1, in part by the Natural Science Foundation of Jiangsu Province under Grant BK20191445, in part by the Six Talent Peaks Project of Jiangsu Province under Grant XYDXXJS-048, and in part by the Qing Lan Project of Jiangsu Province. Paper no. TII-19-4042. (Corresponding author: Linghe Kong.)
Publisher Copyright:
© 2020 IEEE.
PY - 2020/10
Y1 - 2020/10
N2 - 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.
AB - 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.
KW - Blockchain
KW - mobile crowd sensing (MCS)
KW - mobility
KW - scalability
KW - security
KW - smart factory
UR - http://www.scopus.com/inward/record.url?scp=85083462654&partnerID=8YFLogxK
U2 - 10.1109/TII.2019.2963728
DO - 10.1109/TII.2019.2963728
M3 - Journal article
AN - SCOPUS:85083462654
SN - 1551-3203
VL - 16
SP - 6553
EP - 6563
JO - IEEE Transactions on Industrial Informatics
JF - IEEE Transactions on Industrial Informatics
IS - 10
ER -