Cloud security is an important concern. To identify and stop cyber threats, efficient data collection methods are necessary. This research presents an innovative method to cloud security by integrating numerous data sources and modalities with multi-modal deep learning autoencoders. The Multi-Modal Deep Learning Ensemble Architecture (MMDLEA), a unique approach for anomaly detection and classification in multi-modal data, is proposed in this study. The proposed design integrates the best features of six deep learn…