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The Internet of Things is considered to be an emerging trend since it facilitates more effective communication among smart devices. The IoT technology acts as a double‐edged sword that has multiple advantages, along with the advantages, the cyber threats in the network have increased proportionally which initiates the necessity for the manufacturers to provide in‐built security‐enabled physical devices. Therefore, for ensuring IoT security against cyber threats, this research proposed a novel innovative detection method relying on the hybridized ensemble classifier. The classifier is developed through the integration of the Hybrid Forage Optimization (HFO) with the ensembled classifier. The hybrid ensemble classifier is developed based on the hybridization of convolutional neural network (CNN) and long short‐term memory (LSTM) classifiers, which provides more efficiency. The proposed hybrid forage …