Vol.13, No.4, November 2024.                                                                                                                                                                          ISSN: 2217-8309

                                                                                                                                                                                                                      eISSN: 2217-8333

TEM Journal

TECHNOLOGY, EDUCATION, MANAGEMENT, INFORMATICS

Association for Information Communication Technology Education and Science

Role of Artificial Intelligence in Data Protection for Digital Asset Systems: A Review of Recent Development

Mustafa Ababneh, Ayat Aljarrah

© 2024 Mustafa Ababneh, published by UIKTEN. This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License. (CC BY-NC-ND 4.0)

Citation Information: TEM Journal. Volume 13, Issue 4, Pages 3431-3444, ISSN 2217-8309, DOI: 10.18421/TEM134-76, November 2024.

Received: 10 May 2024.

Revised: 07 September 2024.
Accepted: 07 October 2024.
Published: 27 November 2024.

Abstract:

AI integration in digital assets and data protection is revolutionizing asset management. Proper AI applications can enhance security, but regulation must balance innovation and misuse, requiring a thorough understanding of technology. Data protection safeguards sensitive data from loss, alteration, or corruption, ensuring compliance with legal and regulatory obligations. It involves business information procedures and data protection mechanisms, particularly in the financial industry. Restricting access to digital asset data is crucial. This paper systematically reviews the recent role of AI in data protection for digital asset systems. Recent studies have reported enhanced algorithms for data protection in digital assets, focusing on transactions, markets, surveillance, and infrastructure assets. Robust algorithms in the digital asset market improve data protection and address issues with traditional crowdfunding. Token financing is a new strategy aimed at solving these issues. However, startups often lack knowledge about risk when choosing new token financing options. In the future, AI may be able to predict potential threats or vulnerabilities to digital assets through data protection trends and patterns. This would allow proactive data protection measures rather than just reactive ones. It will enhance digital asset systems' functionality and accuracy.

Keywords – Artificial intelligence, data protection, digital assets, DAM.

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