ISSN (Print): 3079-4722 ISSN (Online): 3079-4722
International Journal of Unique and New Updates, Hong Kong, ISSN: 3079-4722 Official Publication of Octopus Publication, Hong Kong
Cover of July-December 2023
research article

Enhancing Data Integrity and Security in Blockchain for AI Tools

  • Ganesh Vadlakonda
    United States

Vol. 5 , Issue 2 (2023) · pp. 1-8

Country: United States

DOI: 10.64180/ijunu.522301

Abstract

In the rapidly evolving landscape of artificial intelligence (AI), ensuring data integrity and security has emerged as a critical concern. This paper explores the integration of blockchain technology as a solution to these challenges, proposing a framework that leverages the decentralized and immutable characteristics of blockchain to enhance the reliability of AI systems. By employing a distributed ledger, the proposed model facilitates transparent data provenance, enabling stakeholders to trace the origin and modifications of data used in AI algorithms. Additionally, the paper examines the mechanisms by which blockchain can safeguard against data tampering and unauthorized access, thereby reinforcing the trustworthiness of AI outputs. Through case studies and practical applications, we illustrate the potential of this blockchain-enabled approach in various sectors, including healthcare, finance, and supply chain management. The findings underscore that the synergistic relationship between blockchain and AI not only bolsters data security but also fosters greater collaboration and innovation across industries, paving the way for more robust and ethical AI solutions.

Keywords: Blockchain Artificial Intelligence (AI) Data Integrity Security Decentralization
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