International Journal For Multidisciplinary Research
E-ISSN: 2582-2160
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Impact Factor: 9.24
A Widely Indexed Open Access Peer Reviewed Multidisciplinary Bi-monthly Scholarly International Journal
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Volume 8 Issue 2
March-April 2026
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Adaptive Security Paradigms: The Role of Al in Safeguarding Distributed Data Across Multi-cloud Platforms
| Author(s) | Phanindra Kalva, Srikanth Padakanti, Sudheer Chennuri |
|---|---|
| Country | United States |
| Abstract | The proliferation of multi-cloud infrastructures in modern data management strategies has introduced complex security challenges that traditional measures struggle to address effectively. This article investigates the potential of AI-powered security frameworks to enhance distributed data protection across diverse cloud environments. By leveraging advanced machine learning algorithms and predictive analytics, these frameworks offer real-time threat detection, adaptive access controls, and intelligent encryption management. The article examines the key components of AI-driven security systems, including automated anomaly detection and behavior analysis, and their integration with existing security protocols. Through a series of case studies and real-world applications, we demonstrate the efficacy of these frameworks in identifying vulnerabilities, initiating proactive security measures, and maintaining compliance with industry regulations. Our findings indicate that AI-powered security frameworks provide a scalable, adaptive, and robust solution for safeguarding distributed data assets in the dynamic landscape of multi-cloud infrastructures. However, the research also acknowledges potential limitations and ethical considerations, paving the way for future advancements in this critical area of cybersecurity. |
| Keywords | Keywords: Multi-cloud security, AI-powered frameworks, Distributed data protection, Machine learning cybersecurity, Adaptive threat detection. |
| Field | Computer |
| Published In | Volume 6, Issue 5, September-October 2024 |
| Published On | 2024-10-31 |
| DOI | https://doi.org/10.36948/ijfmr.2024.v06i05.29551 |
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E-ISSN 2582-2160
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IJFMR DOI prefix is
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