A Review of Deep Learning Techniques for Intrusion Detection in Cloud Computing - M., Duraipandian (Journal of Soft Computing Paradigm, 2026)
The rapid expansion of cloud has computing caused numerous security problems, particularly in distributed designs and resource expansion steps. This situation has led to the development of advanced threat detection mechanisms that exceed the standard signature-based systems. The implementation of these new technologies into security operations is complicated by a number of issues, including limited communication. The effective use of dynamic situations presents additional challenges including concept drift, scalability problems, and real-time delays. This review paper highlights the importance of deep learning for improving cloud security, particularly in intrusion detection systems, which are key components of smart cloud security. This study discusses the deep learning techniques currently in use for cloud intrusion detection, analyses new research topics, and focuses on the continuous limitations in the field. These reviewed techniques will improve the accuracy of protecting cloud computing systems from evolving cyber threats.