Pinned Repositories
Deep-learning-for-intrusion-detection-using-Recurrent-Neural-network-RNN
Deep Learning techniques can be implemented in the field of cybersecurity to handle the issues related to intrusion just as they have been successfully implemented in the areas such as computer vision and natural language processing (NLP). RNN model is compared with J48, Artificial Neural Network, Random Forest, Support Vector Machine and other machine learning techniques to detect malicious attacks in terms of binary and multiclass classifications.
ML-NIDS-for-SCADA
In this work, we aim at developing a NIDS (Network Intrusion Detection System) that detects attacks targeting SCADA systems, in a concrete industrial used case scenario.
NCEPU-zny's Repositories
NCEPU-zny/Deep-learning-for-intrusion-detection-using-Recurrent-Neural-network-RNN
Deep Learning techniques can be implemented in the field of cybersecurity to handle the issues related to intrusion just as they have been successfully implemented in the areas such as computer vision and natural language processing (NLP). RNN model is compared with J48, Artificial Neural Network, Random Forest, Support Vector Machine and other machine learning techniques to detect malicious attacks in terms of binary and multiclass classifications.
NCEPU-zny/ML-NIDS-for-SCADA
In this work, we aim at developing a NIDS (Network Intrusion Detection System) that detects attacks targeting SCADA systems, in a concrete industrial used case scenario.