Privacy-First Crowdsourcing: Blockchain and Local Differential Privacy in Crowdsourced Drone Services

TL;DR

The paper addresses privacy and data protection challenges in crowdsourced drone data for bushfire management by designing a privacy-first marketplace that jointly employs local differential privacy and blockchain-based data exchanges. It integrates local differential privacy to shield drone operators and uses Ethereum smart contracts to provide an immutable, auditable record of data requests, responses, and payments. Key contributions include a local differential privacy framework for crowdsourced drone data, a blockchain-based fair exchange mechanism, a consent feature to foster participation, and a risk-analysis with a proof-of-concept evaluation that demonstrates scalability. The work has practical implications for regulatory compliance, including Australia's Privacy Act 1988, and enhances bushfire detection and management through scalable, privacy-preserving crowdsourced data.

Abstract

We introduce a privacy-preserving framework for integrating consumer-grade drones into bushfire management. This system creates a marketplace where bushfire management authorities obtain essential data from drone operators. Key features include local differential privacy to protect data providers and a blockchain-based solution ensuring fair data exchanges and accountability. The framework is validated through a proof-of-concept implementation, demonstrating its scalability and potential for various large-scale data collection scenarios. This approach addresses privacy concerns and compliance with regulations like Australia's Privacy Act 1988, offering a practical solution for enhancing bushfire detection and management through crowdsourced drone services.

Figures (2)

• Figure 1: System Overview.
• Figure 2: Impact of local differential privacy on data accuracy with different drone counts. Blue line shows the actual response distribution, red line shows the estimated responses post-privacy implementation.