Exploring the Integration of Artificial Intelligence in Detecting Advanced Persistent Threats in Real Time
Keywords:
Artificial Intelligence, Advanced Persistent Threats, Cybersecurity, Real-Time Detection, Machine Learning, Anomaly Detection, Network Security, Threat IntelligenceAbstract
Advanced Persistent Threats (APTs) pose one of the most dangerous challenges to modern cybersecurity systems. Characterized by stealth, persistence, and sophistication, APTs are often orchestrated by state or financially motivated actors targeting sensitive infrastructure. As conventional security tools struggle to provide timely and accurate detection, artificial intelligence (AI) emerges as a transformative solution. This paper explores the integration of AI technologies in detecting APTs in real time, examining architectural frameworks, algorithms, and their performance across various sectors. Through a review of prior literature and recent developments, we highlight how AI-enabled systems are changing the landscape of proactive cybersecurity.
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