The Role of AI in Evolving Data Engineering Practices for Cybersecurity

Abstract

As the cybersecurity landscape continually evolves, so does the need for advanced data engineering practices to mitigate emerging threats and vulnerabilities. Artificial Intelligence (AI) has emerged as a transformative force in enhancing data engineering for cybersecurity, providing sophisticated tools for threat detection, analysis, and response. This paper explores the role of AI in advancing data engineering practices within the realm of cybersecurity, focusing on how AIdriven solutions improve data handling, threat intelligence, and incident response. We discuss various AI techniques, including machine learning, deep learning, and natural language processing, and their application in developing robust cybersecurity frameworks. The integration of AI with data engineering practices facilitates the automation of security processes, real-time threat detection, and predictive analytics, thereby enhancing the overall security posture of organizations. By examining case studies and recent advancements in the field, this paper provides insights into the practical implications of AI-driven data engineering solutions and their impact on cybersecurity effectiveness. The findings underscore the importance of leveraging AI to address the growing complexity of cyber threats and highlight future research directions to further integrate AI into data engineering for cybersecurity.