Detecting command injection attacks in web applications based on novel deep learning methods

This study focuses on detecting web command injection attacks using hybrid deep learning models designed for this purpose. The models, enhanced with attention mechanisms, achieved over 98% accuracy across various datasets, surpassing traditional detection methods. Future plans include adapting the model for tasks like malware detection and phishing prevention, as well as refining it to recognize diverse attack types, including zero-day and DDoS attacks. The research emphasizes AI’s role in advancing network security by offering accurate, adaptable tools to protect web applications. 

https://www.nature.com/articles/s41598-024-74350-3

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