• Samineni Nagamani
• S. Arivalagan

Cloud computing (CC), similar to distributed computing systems, is constantlyvulnerable to numerousrisks and attacksfromdifferentsources. Therefore, cloud safety is currently anessential major problem for eitherproviders or customers. Intrusion detection systems (IDSs) are applied to identifyassaults in these environments. The security administrator’s aim (for either providers or users) is to check and detect attackswhilepreventing disturbance of the smooth action of the cloud. This issueremains pending, and according to our research, there are no acceptable solutions for the automaticanalysis and estimationof cloud security. Deep learning (DL)methods are applied automatically to removenecessarycharacteristics from raw network data that are subsequently fed into a shallow classifier for efficient attack detection.This paper develops a novelDimensionality Reduction-Driven Ensemble Artificial Intelligence Approach for Intrusion Detection in Cloud Environments (DREAIM-IDCE). The main objective of the DREAIM-IDCEtechnique is to enhance real-time ID threat detection and proactive security measures in cloud environments.To accomplish that, the DREAIM-IDCEmethod applies datanormalization stage using Z-score normalization to pre-process the raw network traffic data. For dimensionality reduction, the battle royal optimizer (BRO) algorithm can be employed to extract the most relevant attributes. In addition, an ensemble of attack classification models involving a stacked deep belief network (SDBN), bidirectional gated recurrent unit (BiGRU), and temporal convolutional networks (TCN)are deployed.To further enhance the ensemble models, hyperparameter tuning through the black‐winged kite algorithm (BKA) optimizes model parameters to achieve superior accuracy.A widespreadexperimentalstudy is appliedto guarantee the importance of the DREAIM-IDCEmethod. A short comparativeoutcomeimplied the promising outcomes of the DREAIM-IDCEapproach over other recentmethods.

Intrusion Detection; Cloud Computing; Dimensionality Reduction; Artificial Intelligence; Black‐Winged Kite Algorithm

"Dimensionality Reduction-Driven Ensemble Artificial Intelligence Model for Intrusion Detection in Cloud Environments", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.12, Issue 8, page no.d242-d258, August-2025, Available :http://www.jetir.org/papers/JETIR2508328.pdf

"Dimensionality Reduction-Driven Ensemble Artificial Intelligence Model for Intrusion Detection in Cloud Environments", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.12, Issue 8, page no. ppd242-d258, August-2025, Available at : http://www.jetir.org/papers/JETIR2508328.pdf