AI-Driven Cloud Security: The Future of Safeguarding Sensitive Data in the Digital Age
Hassan Rehan ()
Journal of Artificial Intelligence General science (JAIGS) ISSN:3006-4023, 2024, vol. 1, issue 1, 132-151
Abstract:
As organizations increasingly rely on cloud computing for storage, processing, and deployment of sensitive data, ensuring robust security measures becomes paramount. This paper explores the intersection of artificial intelligence (AI) and cloud security, presenting AI-driven solutions as the future of safeguarding sensitive data in the digital age. Leveraging AI algorithms and machine learning techniques, cloud security can adapt and evolve to counter emerging threats in real-time, enhancing detection, prevention, and response capabilities. This paper discusses various AI-driven approaches to cloud security, including anomaly detection, threat intelligence analysis, and behavior analytics, highlighting their effectiveness in mitigating risks and ensuring compliance with regulatory standards. Additionally, it addresses the challenges and ethical considerations associated with AI-driven cloud security, emphasizing the importance of transparency, accountability, and ethical AI principles. By embracing AI-driven solutions, organizations can fortify their defenses against cyber threats and maintain the integrity and confidentiality of their sensitive data in the evolving digital landscape.
Keywords: AI-driven; Cloud Security; Sensitive Data; Artificial Intelligence (search for similar items in EconPapers)
Date: 2024
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Persistent link: https://EconPapers.repec.org/RePEc:das:njaigs:v:1:y:2024:i:1:p:132-151:id:89
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Journal of Artificial Intelligence General science (JAIGS) ISSN:3006-4023 is currently edited by Justyna Żywiołek
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