Integrative Approaches in Cybersecurity and AI

TL;DR

This paper reviews how integrating AI with cybersecurity and data management can improve security, data analysis, and resilience through automation and real-time threat detection, highlighting key trends and future challenges.

Contribution

It provides a comprehensive analysis of current integrative approaches combining AI with cybersecurity and data management, emphasizing cross-disciplinary strategies and future directions.

Findings

AI-driven automation enhances security responses

Real-time threat detection improves resilience

Advanced data analytics enable better decision-making

Abstract

In recent years, the convergence of cybersecurity, artificial intelligence (AI), and data management has emerged as a critical area of research, driven by the increasing complexity and interdependence of modern technological ecosystems. This paper provides a comprehensive review and analysis of integrative approaches that harness AI techniques to enhance cybersecurity frameworks and optimize data management practices. By exploring the synergies between these domains, we identify key trends, challenges, and future directions that hold the potential to revolutionize the way organizations protect, analyze, and leverage their data. Our findings highlight the necessity of cross-disciplinary strategies that incorporate AI-driven automation, real-time threat detection, and advanced data analytics to build more resilient and adaptive security architectures.