AI-Empowered Security Data Fabrics: Review and Insights on Intelligent Data Pipeline Management
Jaidev Singh · International Journal for Research in Applied Science and Engineering Technology · 2025
Security data fabrics have emerged as pivotal structures to integrate diverse security tools and data sources, providing streamlined, actionable insights. Leveraging artificial intelligence (AI) within intelligent data pipeline management significantly enhances threat detection, prediction, and response capabilities. AI methods such as machine learning, deep learning, and natural language processing automate complex analytical tasks, improve anomaly detection accuracy, and facilitate proactive threat mitigation. This review synthesizes recent developments and evaluates various AI-driven methodologies, emphasizing their impact on operational efficiency, data integrity, and rapid incident response within cybersecurity contexts. The paper critically analyzes current practices, highlights key challenges such as scalability concerns, integration complexity, and ethical considerations related to privacy and bias, and provides concrete proposals for addressing these issues. Furthermore, it discusses emerging trends and proposes future research directions aimed at advancing security data fabric architectures to achieve greater resilience and adaptability against evolving cyber threats.