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Ensuring Compliance Integrity in AI ML Cloud Environments: The Role of Data Guardianship

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  • Samadrita Ghosh

Abstract

Artificial intelligence (AI) has become ubiquitous across various industries, including security, healthcare, finance, and national defense. However, alongside its transformative potential, there has been a concerning rise in malicious exploitation of AI capabilities. Simultaneously, the rapid advancement of cloud computing technology has led to the emergence of cloud-based AI systems. Unfortunately, vulnerabilities inherent in cloud infrastructure also pose security risks to AI services. We recognize the critical role of maintaining the integrity of training data, as any compromise therein directly impacts the effectiveness of AI systems. In response to this challenge, we emphasize the paramount importance of preserving data integrity within AI systems. To address this need, we propose a data integrity architecture guided by the National Institute of Standards and Technology (NIST) cybersecurity framework. Leveraging blockchain technology and smart contracts presents a suitable solution for addressing integrity challenges, given their features of shared and decentralized ledgers. Smart contracts enable automated policy enforcement, facilitate continuous monitoring of data integrity, and help mitigate the risk of data tampering.

Suggested Citation

  • Samadrita Ghosh, 2024. "Ensuring Compliance Integrity in AI ML Cloud Environments: The Role of Data Guardianship," Journal of Artificial Intelligence General science (JAIGS) ISSN:3006-4023, Open Knowledge, vol. 3(1), pages 303-322.
  • Handle: RePEc:das:njaigs:v:3:y:2024:i:1:p:303-322:id:122
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    References listed on IDEAS

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    1. Hassan Rehan, 2024. "AI-Driven Cloud Security: The Future of Safeguarding Sensitive Data in the Digital Age," Journal of Artificial Intelligence General science (JAIGS) ISSN:3006-4023, Open Knowledge, vol. 1(1), pages 132-151.
    2. Mithun Sarker, 2024. "Revolutionizing Healthcare: The Role of Machine Learning in the Health Sector," Journal of Artificial Intelligence General science (JAIGS) ISSN:3006-4023, Open Knowledge, vol. 2(1), pages 36-61.
    3. Hassan Rehan, 2024. "Revolutionizing America's Cloud Computing the Pivotal Role of AI in Driving Innovation and Security," Journal of Artificial Intelligence General science (JAIGS) ISSN:3006-4023, Open Knowledge, vol. 2(1), pages 239-240.
    4. Nicolas Guzman Camacho, 2024. "Unlocking the Potential of AI/ML in DevSecOps: Effective Strategies and Optimal Practices," Journal of Artificial Intelligence General science (JAIGS) ISSN:3006-4023, Open Knowledge, vol. 2(1), pages 91-100.
    5. Jeff Shuford & Md.Mafiqul Islam, 2024. "Exploring Current Trends in Artificial Intelligence Technology An Extensive Review," Journal of Artificial Intelligence General science (JAIGS) ISSN:3006-4023, Open Knowledge, vol. 2(1), pages 1-13.
    6. Md.mafiqul Islam, 2024. "Artificial Intelligence Exploring Its Applications across Industries," Journal of Artificial Intelligence General science (JAIGS) ISSN:3006-4023, Open Knowledge, vol. 2(1), pages 20-24.
    7. Nicolas Guzman Camacho, 2024. "Unlocking the Potential of AI/ML in DevSecOps: Effective Strategies and Optimal Practices," Journal of Artificial Intelligence General science (JAIGS) ISSN:3006-4023, Open Knowledge, vol. 3(1), pages 106-115.
    8. Harish Padmanaban, 2024. "Revolutionizing Regulatory Reporting through AI/ML: Approaches for Enhanced Compliance and Efficiency," Journal of Artificial Intelligence General science (JAIGS) ISSN:3006-4023, Open Knowledge, vol. 2(1), pages 71-90.
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