Enhancing data security and regulatory compliance in AI-driven cloud ecosystems: Strategies for advanced information governance
Independent Researcher, USA.
Research Article
World Journal of Advanced Research and Reviews, 2022, 15(03), 579-594
Article DOI: 10.30574/wjarr.2022.15.3.0905
Publication history:
Received on 04 August 2022; revised on 17 September 2022; accepted on 19 September 2022
Abstract:
This study examines adaptive information governance models to address the key issues of AI-based cloud environments, in the end aiming to enable enhanced data security and regulatory compliance. Conventional governance models fail to respond to complexity issues posed by AI-cloud integration, with this resulting in incident response shortcomings, privacy laws, and regulatory compliance identification. In response to these weaknesses, this research analyzes governance elements such as Privacy-Enhancing Technologies (PETs), ethical regulation, and incident response models using sophisticated quantitative methods such as Structural Equation Modeling (SEM), Cox Proportional Hazards Modeling, and Difference-in-Differences (DiD) analysis.
Results show that incident response effectiveness (β = 0.51, p < 0.001) and PET implementation (β = 0.25, p = 0.001) make noteworthy contributions to the governance outcome, with good model fit indicators (RMSEA = 0.04, CFI = 0.96) demonstrating the viability of the conceptual framework. Sectoral vulnerabilities were unearthed, and retail and technology sectors reported a 25% greater incident threat with less effective controls. Use of PETs, including homomorphic encryption and federated learning, greatly enhanced data utility and privacy compliance, especially for high-risk industries.
The study guides the use of next-generation security controls and PETs to mitigate threats and assist in compliance with regulations, especially in high-security industry. Additionally, ongoing calibration of AI-pushed incident response routines is critical to lessening the effect of ever-evolving cyber threats. Ethical leadership should be made stronger to offer justice, responsibility, and public trust in AI solutions adopted within cloud settings. These strategic recommendations provide an organizations' handbook on how to establish safe, compliant, and ethically regulated AI-based cloud environments.
Keywords:
Information governance; AI-enabled cloud security; Privacy-enhancing technologies; Quantitative risk assessment; Sector-specific compliance
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Copyright © 2022 Author(s) retain the copyright of this article. This article is published under the terms of the Creative Commons Attribution Liscense 4.0