TY - JOUR
T1 - BlockSense: Towards Trustworthy Mobile Crowdsensing via Proof-of-Data Blockchain
AU - Huang, Junqin
AU - Kong, Linghe
AU - Cheng, Long
AU - Dai, Hong Ning
AU - Qiu, Meikang
AU - Chen, Guihai
AU - Liu, Xue
AU - Huang, Gang
N1 - Funding information:
This work was supported in part by NSFC under Grants 62141220, 61972253, U1908212, 72061127001, 62172276, and 61972254, and in part by the Program for Professor of Special Appointment (Eastern Scholar) at Shanghai Institutions of Higher Learning, Open Research Projects of Zhejiang Lab under Grant 2022NL0AB01.
Publisher copyright:
© 2022 IEEE.
PY - 2024/2
Y1 - 2024/2
N2 - Mobile crowdsensing (MCS) can promote data acquisition and sharing among mobile devices. Traditional MCS platforms are based on a triangular structure consisting of three roles: data requester, worker (i.e., sensory data provider) and MCS platform. However, this centralized architecture suffers from poor reliability and difficulties in guaranteeing data quality and privacy, even provides unfair incentives for users. In this article, we propose a blockchain-based MCS platform, namely BlockSense, to replace the traditional triangular architecture of MCS models by a decentralized paradigm. To achieve the goal of trustworthiness of BlockSense, we present a novel consensus protocol, namely Proof-of-Data (PoD), which leverages miners to conduct useful data quality validation work instead of 'useless' hash calculation. Meanwhile, in order to preserve the privacy of the sensory data, we design a homomorphic data perturbation scheme, through which miners can verify data quality without knowing the contents of the data. We have implemented a prototype of BlockSense and conducted case studies on campus, collecting over 7,000 data from workers' mobile phones. Both simulations and real-world experiments show that BlockSense can not only improve system security, preserve data privacy and guarantee incentives fairness, but also achieve at least 5.6x faster than Ethereum smart contracts in verification efficiency.
AB - Mobile crowdsensing (MCS) can promote data acquisition and sharing among mobile devices. Traditional MCS platforms are based on a triangular structure consisting of three roles: data requester, worker (i.e., sensory data provider) and MCS platform. However, this centralized architecture suffers from poor reliability and difficulties in guaranteeing data quality and privacy, even provides unfair incentives for users. In this article, we propose a blockchain-based MCS platform, namely BlockSense, to replace the traditional triangular architecture of MCS models by a decentralized paradigm. To achieve the goal of trustworthiness of BlockSense, we present a novel consensus protocol, namely Proof-of-Data (PoD), which leverages miners to conduct useful data quality validation work instead of 'useless' hash calculation. Meanwhile, in order to preserve the privacy of the sensory data, we design a homomorphic data perturbation scheme, through which miners can verify data quality without knowing the contents of the data. We have implemented a prototype of BlockSense and conducted case studies on campus, collecting over 7,000 data from workers' mobile phones. Both simulations and real-world experiments show that BlockSense can not only improve system security, preserve data privacy and guarantee incentives fairness, but also achieve at least 5.6x faster than Ethereum smart contracts in verification efficiency.
KW - Blockchain
KW - Consensus
KW - Mobile crowdsensing
KW - Privacy
KW - Proof of useful work
KW - Verifiable computation
UR - http://www.scopus.com/inward/record.url?scp=85146251439&partnerID=8YFLogxK
U2 - 10.1109/TMC.2022.3230758
DO - 10.1109/TMC.2022.3230758
M3 - Journal article
SN - 1536-1233
VL - 23
SP - 1016
EP - 1033
JO - IEEE Transactions on Mobile Computing
JF - IEEE Transactions on Mobile Computing
IS - 2
ER -