Cybersecurity of Sensor Systems for State Sequence Estimation A Machine Learning Approch
Objective
“The objective of this project is to develop a machine learning–based cybersecurity framework for securing sensor systems and state sequence estimation. The system uses Random Forest, XGBoost, Extra Trees, LightGBM, and K-Nearest Neighbors (KNN) algorithms, along with a Hybrid Model, to classify network traffic into Benign and Attack classes. It aims to improve intrusion detection accuracy, enhance threat mitigation, and provide real-time security recommendations.”
Paper Publishing
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