A Blockchain-Enhanced Framework for Privacy and Data Integrity in Crowdsourced Drone Services
- URL: http://arxiv.org/abs/2410.05653v1
- Date: Tue, 8 Oct 2024 03:08:47 GMT
- Title: A Blockchain-Enhanced Framework for Privacy and Data Integrity in Crowdsourced Drone Services
- Authors: Junaid Akram, Ali Anaissi,
- Abstract summary: We present an innovative framework that integrates consumer-grade drones into bushfire management, addressing both service improvement and data privacy concerns under Australia's Privacy Act 1988.
This system establishes a marketplace where bushfire management authorities, as data consumers, access critical information from drone operators, who serve as data providers.
The framework employs local differential privacy to safeguard the privacy of data providers from all system entities, ensuring compliance with privacy standards.
- Score: 0.6284464997330884
- License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
- Abstract: We present an innovative framework that integrates consumer-grade drones into bushfire management, addressing both service improvement and data privacy concerns under Australia's Privacy Act 1988. This system establishes a marketplace where bushfire management authorities, as data consumers, access critical information from drone operators, who serve as data providers. The framework employs local differential privacy to safeguard the privacy of data providers from all system entities, ensuring compliance with privacy standards. Additionally, a blockchain-based solution facilitates fair data and fee exchanges while maintaining immutable records for enhanced accountability. Validated through a proof-of-concept implementation, the framework's scalability and adaptability make it well-suited for large-scale, real-world applications in bushfire management.
Related papers
- Towards Personal Data Sharing Autonomy:A Task-driven Data Capsule Sharing System [5.076862984714449]
We introduce a novel task-driven personal data sharing system based on the data capsule paradigm realizing personal data sharing autonomy.
Specifically, we present a tamper-resistant data capsule encapsulation method, where the data capsule is the minimal unit for independent and secure personal data storage and sharing.
arXiv Detail & Related papers (2024-09-27T05:13:33Z) - Privacy-First Crowdsourcing: Blockchain and Local Differential Privacy in Crowdsourced Drone Services [0.6284464997330884]
We introduce a privacy-preserving framework for integrating consumer-grade drones into bushfire management.
Key features include local differential privacy to protect data providers and a blockchain-based solution ensuring fair data exchanges and accountability.
arXiv Detail & Related papers (2024-07-01T00:46:25Z) - Marking the Pace: A Blockchain-Enhanced Privacy-Traceable Strategy for Federated Recommender Systems [11.544642210389894]
Federated recommender systems have been enhanced through data sharing and continuous model updates.
Given the sensitivity of IoT data, transparent data processing in data sharing and model updates is paramount.
Existing methods fall short in tracing the flow of shared data and the evolution of model updates.
We present LIBERATE, a privacy-traceable federated recommender system.
arXiv Detail & Related papers (2024-06-07T07:21:21Z) - FACOS: Enabling Privacy Protection Through Fine-Grained Access Control with On-chain and Off-chain System [11.901770945295391]
We propose a permissioned blockchain-based privacy-preserving fine-grained access control on-chain and off-chain system, namely FACOS.
Compared to similar work that only stores encrypted data in centralized or non-fault-tolerant IPFS systems, we enhanced off-chain data storage security and robustness.
arXiv Detail & Related papers (2024-06-06T02:23:12Z) - Blockchain-enabled Data Governance for Privacy-Preserved Sharing of Confidential Data [1.6006586061577806]
We propose a blockchain-based data governance system that employs attribute-based encryption to prevent privacy leakage and credential misuse.
First, our ABE encryption system can handle multi-authority use cases while protecting identity privacy and hiding access policy.
Second, applying the Advanced Encryption Standard (AES) for data encryption makes the whole system efficient and responsive to real-world conditions.
arXiv Detail & Related papers (2023-09-08T05:01:59Z) - Blockchain-empowered Federated Learning for Healthcare Metaverses:
User-centric Incentive Mechanism with Optimal Data Freshness [66.3982155172418]
We first design a user-centric privacy-preserving framework based on decentralized Federated Learning (FL) for healthcare metaverses.
We then utilize Age of Information (AoI) as an effective data-freshness metric and propose an AoI-based contract theory model under Prospect Theory (PT) to motivate sensing data sharing.
arXiv Detail & Related papers (2023-07-29T12:54:03Z) - Protecting User Privacy in Online Settings via Supervised Learning [69.38374877559423]
We design an intelligent approach to online privacy protection that leverages supervised learning.
By detecting and blocking data collection that might infringe on a user's privacy, we can restore a degree of digital privacy to the user.
arXiv Detail & Related papers (2023-04-06T05:20:16Z) - Privacy-Preserving Joint Edge Association and Power Optimization for the
Internet of Vehicles via Federated Multi-Agent Reinforcement Learning [74.53077322713548]
We investigate the privacy-preserving joint edge association and power allocation problem.
The proposed solution strikes a compelling trade-off, while preserving a higher privacy level than the state-of-the-art solutions.
arXiv Detail & Related papers (2023-01-26T10:09:23Z) - Second layer data governance for permissioned blockchains: the privacy
management challenge [58.720142291102135]
In pandemic situations, such as the COVID-19 and Ebola outbreak, the action related to sharing health data is crucial to avoid the massive infection and decrease the number of deaths.
In this sense, permissioned blockchain technology emerges to empower users to get their rights providing data ownership, transparency, and security through an immutable, unified, and distributed database ruled by smart contracts.
arXiv Detail & Related papers (2020-10-22T13:19:38Z) - Give more data, awareness and control to individual citizens, and they
will help COVID-19 containment [74.10257867142049]
Contact-tracing apps are being proposed for large scale adoption by many countries.
A centralized approach raises concerns about citizens' privacy and needlessly strong digital surveillance.
We advocate a decentralized approach, where both contact and location data are collected exclusively in individual citizens' "personal data stores"
arXiv Detail & Related papers (2020-04-10T20:30:37Z) - Beyond privacy regulations: an ethical approach to data usage in
transportation [64.86110095869176]
We describe how Federated Machine Learning can be applied to the transportation sector.
We see Federated Learning as a method that enables us to process privacy-sensitive data, while respecting customer's privacy.
arXiv Detail & Related papers (2020-04-01T15:10:12Z)
This list is automatically generated from the titles and abstracts of the papers in this site.
This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.