Computer networks cybersecurity monitoring based on CNN-LSTM model
Rasim Mahammad Alguliyev, Ramiz Shikhaliyev · 2024
Cybersecurity monitoring is essential for safeguarding computer networks. However, the increasing scale, complexity, and data volume of modern networks present significant challenges for traditional monitoring methods. To address these challenges, we propose a deep learning-based method for network security monitoring. Our method integrates convolutional neural networks (CNNs) with long short-term memory (LSTM) models. Trained on the CICIDS2017 dataset, the proposed model achieved a classification accuracy of 96.76% and an error rate of 9.34%, showcasing its effectiveness in managing complex and voluminous network data.