Neuro-symbolic ai for cloud intrusion detection: A hybrid intelligence approach

Gajjar, Shraddhaben R. (2025) Neuro-symbolic ai for cloud intrusion detection: A hybrid intelligence approach. GSC Advanced Research and Reviews, 22 (2). pp. 142-144. ISSN 2582-4597

As cloud computing becomes more prevalent, ensuring robust cybersecurity is an ongoing challenge. Traditional intrusion detection systems (IDS) often struggle to keep pace with emerging cyber threats due to their reliance on static rule-based mechanisms. Neuro-Symbolic AI presents a hybrid intelligence approach that merges deep learning (neural networks) with symbolic reasoning, offering enhanced accuracy, explainability, and adaptability in intrusion detection. This paper investigates the role of Neuro-Symbolic AI in cloud security, detailing its application in threat detection, real-time response, and compliance management. Additionally, we explore its role in proactive threat intelligence, real-world implementation challenges, and emerging trends in AI-driven security models.