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Deep Learning-Based Anomaly Detection For Cyber Threats in Critical Infrastructure Systems by raghadmosaimi is a document available to read on EtoBox.

What is Deep Learning-Based Anomaly Detection For Cyber Threats in Critical Infrastructure Systems about?

This study investigates the use of deep learning techniques for anomaly detection in critical infrastructure systems to enhance cybersecurity against cyber threats. It evaluates various architectures, including Autoencoders, CNNs, and RNNs, revealing that Autoencoders excel in detecting subtle anomalies with low false positive rates, while LSTMs are effective in capturing temporal dependencies. The findings suggest that deep learning models significantly improve anomaly detection capabilities compared to tr

Author

raghadmosaimi

Language

EN