Journal of Intelligent Systems and Internet of Things JISIoT 2690-6791 2769-786X 10.54216/JISIoT https://www.americaspg.com/journals/show/3934 2019 2019 Biomedical Informatics College, University of information Technology and Communication, Iraq Waleed Waleed Biomedical Informatics College, University of information Technology and Communication, Iraq Ghaith J. Mohammed Biomedical Informatics College, University of information Technology and Communication, Iraq Ahmed Salih Al Al-Obaidi Faculty of Information and Communication Technology, Universiti Teknikal Malaysia Melaka, Malaysia Massila Kamalrudin Center of Research and Innovation Management, Universiti Teknikal Malaysia Melaka, Malaysia Mustafa Musa Malicious activities that seek to disrupt cloud communication are cybersecurity threats. Nevertheless, none of the existing works focused on detecting the attacks that happened in the Blade Server (BS) in the cloud. Therefore, this paper proposes an efficient Intrusion Detection System (IDS) framework for BS in the cloud by utilizing Kerberos-based Exponential Mestre-Brainstrass Curve Cryptography (KEMBCC) and Sechsoftwave and Sparsele-centric Gated Recurrent Unit (SSGRU). Primarily, the cloud users are registered into the network. Then, the incoming data are encrypted. Here, to balance the incoming loads, BS is used. To detect attacks in BS, IDS is implemented. Initially, the data are preprocessed. Further, the big data are handled in the IDS. Afterward, the features are extracted and optimal features are chosen from it. Thereafter, to classify the attack and normal BS, the SSGRU classifier is used. After that, by generating a Sankey diagram, the attacked and non-attacked blades in the BS are differentiated. Next, the attacked blades are isolated, whereas the non-attacked blades are further used for load balancing on the cloud. According to the analysis results, this model performed superior to the other models by attaining an accuracy of 99.43%. 2026 2026 48 63 10.54216/JISIoT.180104 https://www.americaspg.com/articleinfo/18/show/3934