Cyber threats targeting Industrial Internet of Things (IIoT) systems pose significant risks to critical infrastructure security. SmartSentry presents a comprehensive Cyber Threat Intelligence (CTI) framework tailored for IIoT environments. This framework integrates advanced machine learning algorithms and deep learning architectures to detect and mitigate cyber threats effectively. Key algorithms include Random Forest (RF), Decision Tree (DT), Extra Tree Classifier (ETC), Support Vector Machine (SVM), k-Nearest Neighbor (KNN), and Deep Neural Network (DNN). Techniques such as Synthetic Minority Over-sampling Technique (SMOTE) enhance model robustness against imbalanced data, crucial in IIoT anomaly detection. SmartSentry's approach leverages real-time data analysis and anomaly detection to preemptively identify and respond to threats, ensuring continuous operational integrity and resilience of IIoT infrastructures.

Keywords: IIoT, Cyber Threat Intelligence, Machine Learning, Deep Learning, Anomaly Detection, Random Forest, Decision Tree, Support Vector Machine, k-Nearest Neighbor