Md Arifur Rahman
4 indexed papers
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The paper proposes CANGuard, a hybrid CNN-GRU-Attention deep learning model, to accurately detect sophisticated Denial-of-Service and spoofing attacks targeting critical in-vehicle CAN bus networks.
This paper proposes a hybrid CNN-LSTM framework to enhance cyber attack detection and prevention in U.S. critical digital infrastructure by evaluating multiple machine learning models on the CSE-CIC-IDS2018 dataset.
This paper proposes an Explainable AI (XAI)-driven framework using XGBoost and SHAP to enhance cyber risk analytics and model reliability for intelligent governance of U.S. critical infrastructure.
The paper proposes a Cognitive Threat Intelligence and Explainable Federated Security Analytics framework to enable privacy-preserving and scalable cyber threat detection across distributed infrastructure systems.
Papers
Hybrid CNN-LSTM Framework for Intelligent Cyber Attack Detection and Prevention in U.S. Critical Digital Infrastructure: A Comparative Machine Learning Evaluation on CSE-CIC-IDS2018
This paper proposes a hybrid CNN-LSTM framework to enhance cyber attack detection and prevention in U.S. critical digital infrastructure by evaluating multiple machine learning models on the CSE-CIC-I…