Content area

Abstract

The article aims to investigate the potential of blockchain technology in mitigating certain cybersecurity risks associated with artificial intelligence (AI) systems. Aligned with ongoing regulatory deliberations within the European Union (EU) and the escalating demand for more resilient cybersecurity measures within the realm of AI, our analysis focuses on specific requirements outlined in the proposed AI Act. We argue that by leveraging blockchain technology, AI systems can align with some of the requirements in the AI Act, specifically relating to data governance, record-keeping, transparency and access control. The study shows how blockchain can successfully address certain attack vectors related to AI systems, such as data poisoning in trained AI models and data sets. Likewise, the article explores how specific parameters can be incorporated to restrict access to critical AI systems, with private keys enforcing these conditions through tamper-proof infrastructure. Additionally, the article analyses how blockchain can facilitate independent audits and verification of AI system behaviour. Overall, this article sheds light on the potential of blockchain technology in fortifying high-risk AI systems against cyber risks, contributing to the advancement of secure and trustworthy AI deployments. By providing an interdisciplinary perspective of cybersecurity in the AI domain, we aim to bridge the gap that exists between legal and technical research, supporting policy makers in their regulatory decisions concerning AI cyber risk management.

Details

Identifier / keyword
Title
Blockchain for Artificial Intelligence (AI): enhancing compliance with the EU AI Act through distributed ledger technology. A cybersecurity perspective
Author
Ramos, Simona 1 ; Ellul, Joshua 2 

 University Pompeu Fabra, Department of Information and Communication Technologies Engineering (ETIC), Barcelona, Spain (GRID:grid.5612.0) (ISNI:0000 0001 2172 2676) 
 University of Malta, Centre for Distributed Ledger Technologies, Msida, Malta (GRID:grid.4462.4) (ISNI:0000 0001 2176 9482) 
Publication title
Volume
5
Issue
1
Pages
1-20
Publication year
2024
Publication date
Mar 2024
Publisher
Springer Nature B.V.
Place of publication
Wiesbaden
Country of publication
Netherlands
Publication subject
ISSN
26629720
e-ISSN
26629739
Source type
Scholarly Journal
Language of publication
English
Document type
Journal Article
Publication history
 
 
Online publication date
2024-01-25
Milestone dates
2023-12-18 (Registration); 2023-08-09 (Received); 2023-12-01 (Accepted)
Publication history
 
 
   First posting date
25 Jan 2024
ProQuest document ID
3255264336
Document URL
https://www.proquest.com/scholarly-journals/blockchain-artificial-intelligence-ai-enhancing/docview/3255264336/se-2?accountid=208611
Copyright
© The Author(s) 2024. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.
Last updated
2025-09-29
Database
2 databases
  • ProQuest One Academic
  • ProQuest One Academic