Smart Contract Coordinated Privacy Preserving Crowd-Sensing Campaigns

TL;DR

This paper introduces a blockchain-based system using smart contracts to manage privacy-preserving crowd-sensing campaigns, enhancing security, decentralization, and user incentives.

Contribution

It presents a novel smart contract framework for decentralized crowd-sensing that improves privacy, security, and incentivization over traditional centralized methods.

Findings

Simulation confirms system viability.

User participation is crucial for data credibility.

Geographical data scarcity affects rewards.

Abstract

Crowd-sensing has emerged as a powerful data retrieval model, enabling diverse applications by leveraging active user participation. However, data availability and privacy concerns pose significant challenges. Traditional methods like data encryption and anonymization, while essential, may not fully address these issues. For instance, in sparsely populated areas, anonymized data can still be traced back to individual users. Additionally, the volume of data generated by users can reveal their identities. To develop credible crowd-sensing systems, data must be anonymized, aggregated and separated into uniformly sized chunks. Furthermore, decentralizing the data management process, rather than relying on a single server, can enhance security and trust. This paper proposes a system utilizing smart contracts and blockchain technologies to manage crowd-sensing campaigns. The smart contract handles user subscriptions, data encryption, and decentralized storage, creating a secure data marketplace. Incentive policies within the smart contract encourage user participation and data diversity. Simulation results confirm the system's viability, highlighting the importance of user participation for data credibility and the impact of geographical data scarcity on rewards. This approach aims to balance data origin and reduce cheating risks.