Cloud Data Centre Security Using RNN, CNN, and LSTM for Anomaly and Intruder Detection: A Review

. Cloud data centres are critical infrastructures that store and process massive volumes of sensitive data. With the rapid growth of cloud computing, security threats such as intrusions, Distributed Denial of Service (DDoS) attacks, malware injection, and insider attacks have significantly increased. Traditional rule-based intrusion detection systems (IDS) struggle to detect sophisticated and zero-day attacks. Deep learning techniques such as Recurrent Neural Networks (RNN), Convolutional Neural Networks (CNN), and Long Short-Term Memory (LSTM) networks have emerged as powerful tools for anomaly and intruder detection. This paper reviews recent advancements in deep learning-based security mechanisms for cloud data centres. It analyzes architectures, datasets, performance metrics, advantages, limitations, and future research directions.