Integrating Artificial Intelligence and Big Data Analytics for Enhanced Cybersecurity

Abstract

The exponential growth of digital information has brought increased challenges in maintaining cybersecurity. Artificial Intelligence (AI) and Big Data Analytics have emerged as powerful tools to combat cyber threats by detecting anomalies, predicting attacks, and automating response mechanisms. This paper explores the integration of AI models such as machine learning and deep learning with Big Data frameworks like Hadoop and Spark to enhance cybersecurity systems. It highlights various techniques, including intrusion detection, threat analysis, and automated responses. The study provides a comprehensive overview of current trends, challenges, and future directions in AI-driven cybersecurity frameworks. Furthermore, it emphasizes the need for real-time data processing and adaptive learning to identify and mitigate cyber threats efficiently. The paper discusses practical applications across industries, including financial institutions, government agencies, and healthcare organizations.

Keywords: Artificial Intelligence, Big Data Analytics, Cybersecurity, Intrusion Detection, Threat Mitigation