The Role of Artificial Intelligence in Predicting Cybersecurity Threats: Integrating Machine Learning with Traditional Security Frameworks
DOI:
https://doi.org/10.63282/3050-9262.IJAIDSML-V3I4P102Keywords:
AI in cybersecurity, machine learning, threat detection, anomaly detection, supervised learning, unsupervised learning, adversarial attacks, network security, predictive analytics, threat responseAbstract
The rapid evolution of cyber threats has outpaced traditional cybersecurity measures, necessitating the integration of advanced technologies such as Artificial Intelligence (AI) and Machine Learning (ML). This paper explores the role of AI in predicting cybersecurity threats and the integration of ML with traditional security frameworks. We discuss the theoretical foundations, practical applications, and the challenges and benefits of this integration. Through a review of existing literature and case studies, we highlight the effectiveness of AI and ML in enhancing threat detection and response mechanisms. The paper also presents a detailed algorithm for a predictive threat detection system and discusses future research directions
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