аналитика - Network Security
General In-Network Unsupervised Intrusion Detection by Rule Extraction
Genos, a general in-network framework for unsupervised anomaly-based network intrusion detection, achieves high throughput, interpretability, and trivial updating overhead by extracting model-agnostic rules.
Addressing Class Imbalance in Bot-IoT Dataset for Effective Network Intrusion Detection
To address the class imbalance problem in the Bot-IoT dataset, a binary classification method with synthetic minority over-sampling techniques (SMOTE) is proposed to effectively detect attack packets in IoT network traffic.