A Survey of Blockchain-Based Privacy Applications: An Analysis of Consent Management and Self-Sovereign Identity Approaches
- URL: http://arxiv.org/abs/2411.16404v1
- Date: Mon, 25 Nov 2024 14:10:30 GMT
- Title: A Survey of Blockchain-Based Privacy Applications: An Analysis of Consent Management and Self-Sovereign Identity Approaches
- Authors: Rodrigo Dutra Garcia, Gowri Ramachandran, Kealan Dunnett, Raja Jurdak, Caetano Ranieri, Bhaskar Krishnamachari, Jo Ueyama,
- Abstract summary: Modern distributed applications leverage advanced artificial intelligence (AI) and machine learning algorithms to automate business processes.
The proliferation of AI technologies increases data demand in realworld networks.
While technology offers auditability, immutability for multi-stakeholder applications, it lacks inherent support for privacy.
This article surveys the literature on blockchain-based privacy systems and identifies the tools for protecting privacy.
- Score: 6.727433982111718
- License:
- Abstract: Modern distributed applications in healthcare, supply chain, and the Internet of Things handle a large amount of data in a diverse application setting with multiple stakeholders. Such applications leverage advanced artificial intelligence (AI) and machine learning algorithms to automate business processes. The proliferation of modern AI technologies increases the data demand. However, real-world networks often include private and sensitive information of businesses, users, and other organizations. Emerging data-protection regulations such as the General Data Protection Regulation (GDPR) and the California Consumer Privacy Act (CCPA) introduce policies around collecting, storing, and managing digital data. While Blockchain technology offers transparency, auditability, and immutability for multi-stakeholder applications, it lacks inherent support for privacy. Typically, privacy support is added to a blockchain-based application by incorporating cryptographic schemes, consent mechanisms, and self-sovereign identity. This article surveys the literature on blockchain-based privacy-preserving systems and identifies the tools for protecting privacy. Besides, consent mechanisms and identity management in the context of blockchain-based systems are also analyzed. The article concludes by highlighting the list of open challenges and further research opportunities.
Related papers
- Private Blockchain-based Procurement and Asset Management System with QR Code [0.0]
The developed system aims to incorporate a private blockchain technology in the procurement process for the supply office.
The procurement process includes the canvassing, purchasing, delivery and inspection of items, inventory, and disposal.
The study recommends the use of private blockchain-based technology with the procurement and asset management system in the supply office.
arXiv Detail & Related papers (2024-07-12T15:27:36Z) - CAKE: Sharing Slices of Confidential Data on Blockchain [1.481195148653669]
Control Access via Key Encryption (CAKE) designed to ensure data confidentiality in scenarios involving public blockchains.
We showcase the application of CAKE in the context of a real-world cyber-security project within the logistics domain.
arXiv Detail & Related papers (2024-05-07T09:44:04Z) - Enhancing Trust and Privacy in Distributed Networks: A Comprehensive Survey on Blockchain-based Federated Learning [51.13534069758711]
Decentralized approaches like blockchain offer a compelling solution by implementing a consensus mechanism among multiple entities.
Federated Learning (FL) enables participants to collaboratively train models while safeguarding data privacy.
This paper investigates the synergy between blockchain's security features and FL's privacy-preserving model training capabilities.
arXiv Detail & Related papers (2024-03-28T07:08:26Z) - Generative AI-enabled Blockchain Networks: Fundamentals, Applications,
and Case Study [73.87110604150315]
Generative Artificial Intelligence (GAI) has emerged as a promising solution to address challenges of blockchain technology.
In this paper, we first introduce GAI techniques, outline their applications, and discuss existing solutions for integrating GAI into blockchains.
arXiv Detail & Related papers (2024-01-28T10:46:17Z) - Enabling Data Confidentiality with Public Blockchains [5.749927436954179]
Multi-Authority Approach to Transaction Systems for Interoperating Applications (MARTSIA)
MARTSIA enables read-access control over shared data at the level of message parts.
Based on Multi-Authority Attribute-Based Encryption (MA-ABE), MARTSIA enables read-access control over shared data at the level of message parts.
arXiv Detail & Related papers (2023-08-04T13:21:48Z) - An Overview of AI and Blockchain Integration for Privacy-Preserving [1.0155633074816937]
This paper presents an overview of AI and blockchain, summarizing their combination along with derived privacy protection technologies.
It then explores specific application scenarios in data encryption, de-identification, multi-tier distributed ledgers, and k-anonymity methods.
The paper evaluates five critical aspects of AI-blockchain-integration privacy protection systems, including authorization management, access control, data protection, network security, and scalability.
arXiv Detail & Related papers (2023-05-06T04:56:45Z) - Having your Privacy Cake and Eating it Too: Platform-supported Auditing
of Social Media Algorithms for Public Interest [70.02478301291264]
Social media platforms curate access to information and opportunities, and so play a critical role in shaping public discourse.
Prior studies have used black-box methods to show that these algorithms can lead to biased or discriminatory outcomes.
We propose a new method for platform-supported auditing that can meet the goals of the proposed legislation.
arXiv Detail & Related papers (2022-07-18T17:32:35Z) - APPFLChain: A Privacy Protection Distributed Artificial-Intelligence
Architecture Based on Federated Learning and Consortium Blockchain [6.054775780656853]
We propose a new system architecture called APPFLChain.
It is an integrated architecture of a Hyperledger Fabric-based blockchain and a federated-learning paradigm.
Our new system can maintain a high degree of security and privacy as users do not need to share sensitive personal information to the server.
arXiv Detail & Related papers (2022-06-26T05:30:07Z) - 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) - Trustworthy AI Inference Systems: An Industry Research View [58.000323504158054]
We provide an industry research view for approaching the design, deployment, and operation of trustworthy AI inference systems.
We highlight opportunities and challenges in AI systems using trusted execution environments.
We outline areas of further development that require the global collective attention of industry, academia, and government researchers.
arXiv Detail & Related papers (2020-08-10T23:05:55Z) - A vision for global privacy bridges: Technical and legal measures for
international data markets [77.34726150561087]
Despite data protection laws and an acknowledged right to privacy, trading personal information has become a business equated with "trading oil"
An open conflict is arising between business demands for data and a desire for privacy.
We propose and test a vision of a personal information market with privacy.
arXiv Detail & Related papers (2020-05-13T13:55:50Z)
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.