ICETETI-2024 | View PDF
Paper Id:ICETETI-MSM149
doi: 10.71141/30485037/ICETETI-MSM149

Artificial Intelligence Applications for Improving Data Privacy in Backup Systems

Charlotte Davis, Syed Ali Fathima

Citation:
Charlotte Davis, Syed Ali Fathima, "Artificial Intelligence Applications for Improving Data Privacy in Backup Systems", International Journal of Multidisciplinary on Science and Management, pp. 339-344, 2024.

Abstract:
Data privacy has become a crucial aspect of modern backup systems due to increasing cyber threats and stringent regulatory requirements. Artificial Intelligence (AI) is revolutionizing data privacy by introducing automated threat detection, encryption management, and intelligent access control mechanisms. This paper explores AI-driven techniques that enhance data privacy in backup systems, including deep learning for anomaly detection, AI-powered encryption algorithms, and privacy-preserving AI models. A comparative analysis of traditional vs. AI-driven backup privacy mechanisms is presented, highlighting AI's advantages in security, efficiency, and compliance. Experimental results demonstrate AI's effectiveness in mitigating privacy risks and ensuring robust data protection.

Keywords: Artificial Intelligence, Data Privacy, Backup Systems, Encryption, Cybersecurity, Machine Learning, Anomaly Detection, Access Control.

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