Ensuring Incentive Compatibility Through an Improved All-Pay Auction Model for User Recruitment

Crowdsensing leverages a vast number of intelligent terminals and participants to collect, transmit, and analyze data, thereby enabling the perception and processing of information. In this context, user collusion can severely compromise system performance, data accuracy, and fairness. Existing auction-based schemes designed to prevent collusion often lack transparency, enabling colluding users to exploit system rules during the auction process. This not only accelerates the degradation of the system’s ecosystem but also reduces the willingness of other users to participate. Therefore, these schemes are not only ineffective in curbing user collusion but also fail to ensure the accuracy of data. To address this issue, this paper combines the all-pay bidding mechanism with virtual points and proposes a user recruitment mechanism based on all-pay auctions that satisfies incentive compatibility. Theoretical analysis and experimental results confirm that this mechanism can maintain user participation enthusiasm while effectively improving the base and accuracy of data.