An anonymous reputation management system for mobile crowdsensing based on dual blockchain

• Main Authors: WU, Hao-Tian, ZHENG, Yuchong, ZHAO, Bowen, HU, Jianjun
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2022
• Subjects: Blockchains; Sensors; Task analysis; Public key; Servers; Privacy; Peer-to-peer computing; Anonymity; dual blockchain; mobile crowdsensing (MCS); privacy preservation; reputation management; Information Security; Numerical Analysis and Scientific Computing
• Online Access: https://ink.library.smu.edu.sg/sis_research/7593
• Institution: Singapore Management University

In mobile crowdsensing (MCS), sensing data uploaded by dishonest workers may be false or even malicious. Thus, a reputation management system is often set up by using workers' historical behaviors to indicate the quality of sensing data. As existing management schemes usually protect the reputation update process, reputation scores are generally stored in plaintext, which may destroy the fair bidding property of an MCS system. To address this issue, we propose an anonymous reputation management system based on the dual blockchain architecture, where reputation scores are masked. More precisely, one chain is used to store and update reputation scores, and another chain is responsible for publishing tasks and storing task-related data. To anonymously update and verify the reputation scores without affecting their usages in data sensing process, a kind of ring signature and Pedersen commitment is employed in smart contracts. In addition, a Schnorr signature is generated to make the reputation scores verifiable in the MCS system. We implement a prototype system on Hyperledger Fabric, and simulation results are provided for comparisons with two existing schemes.