ICETETI-2024 | View PDF
Paper Id:ICETETI-MSM131
doi: 10.71141/30485037/ICETETI-MSM131

AI-Powered Threat Detection and Security Measures for Backup Systems in Critical Infrastructure

Sophie Clark, Muhammadu Sathik Raja

Citation:
Sophie Clark, Muhammadu Sathik Raja, "AI-Powered Threat Detection and Security Measures for Backup Systems in Critical Infrastructure", International Journal of Multidisciplinary on Science and Management, pp. 233-238, 2024.

Abstract:
Backup systems play a crucial role in maintaining the resilience of critical infrastructure against cyber threats. As cyberattacks become increasingly sophisticated, conventional security methods struggle to provide sufficient protection. AI-powered threat detection offers a proactive and adaptive approach to securing backup systems through machine learning, anomaly detection, and automated response mechanisms. This paper explores AI-driven security solutions, evaluating their effectiveness in threat mitigation and risk management. A comparative analysis with traditional methods highlights AI's advantages in accuracy, real-time detection, and reducing false positives. The methodology outlines a structured framework for implementing AI-powered security, including data preprocessing, model training, and real-world testing. Results demonstrate the efficacy of AI-enhanced systems in improving data integrity, reducing attack vectors, and enhancing overall cybersecurity resilience. Future research will focus on refining AI models, incorporating deep learning, and developing federated learning approaches to ensure robust backup system security.

Keywords: AI-Powered Threat Detection, Backup System Security, Critical Infrastructure, Cybersecurity, Machine Learning, Anomaly Detection, Data Integrity, Encryption, Risk Mitigation, Automated Defense Mechanisms.

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