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

TL;DR

This paper presents a privacy-preserving framework for drone-based data collection in bushfire management, combining blockchain and local differential privacy to ensure secure, fair, and compliant data exchanges.

Contribution

It introduces a novel integration of blockchain and local differential privacy for secure, accountable crowdsourced drone data collection in emergency management.

Findings

Framework is scalable and effective in protecting privacy.

Proof-of-concept demonstrates practical applicability.

Addresses privacy regulation compliance in drone data sharing.

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.