Revolutionizing Data Management: Next-Generation Enterprise Storage Technologies for Scalability and Resilience

Abstract

Ransomware attacks pose a significant threat to organizations, often leading to severe financial losses, data breaches, and operational disruptions. This paper explores how predictive analytics and artificial intelligence (AI) can be leveraged to enhance ransomware resilience, enabling proactive prevention and mitigation of data breaches. By analyzing historical attack patterns, system vulnerabilities, and user behavior, predictive analytics identifies potential threats before they materialize. AI-driven solutions further bolster this approach by employing machine learning models to detect anomalous activities, automate threat response, and implement adaptive security measures in real time. Case studies and experimental results demonstrate the efficacy of integrating these technologies in reducing attack vectors and improving data security. The study concludes with recommendations for adopting predictive analytics and AI frameworks as part of a comprehensive cybersecurity strategy for ransomware resilience.