Jun 13, 2019 · The numerical experiments based on two datasets, KDD99, and CICIDS2017, demonstrate that the key performance in DoS attack detection including ...
Jun 18, 2019 · The numerical experiments based on two datasets, KDD99 and CICIDS2017, demonstrate that the key performance in DoS attack detection including ...
Statistics-Enhanced Direct Batch Growth Self-Organizing Mapping for Efficient DoS Attack Detection ... Statistics for Efficient Network Intrusion Detection.
SandroMartens/DBGSOM: A Python implementation of the ... - GitHub
github.com › SandroMartens › DBGSOM
DBGSOM is short for Directed Batch Growing Self-Organizing Map. A SOM is a type of artificial neural network that is used to to produce a low-dimensional ...
... self-organizing maps for unsupervised intrusion detection ... Statistics-enhanced direct batch growth self-organizing mapping for efficient DoS attack detection.
Statistics-Enhanced Direct Batch Growth Self-Organizing Mapping for Efficient DoS Attack Detection. IEEE Access. 2019 | Journal article. DOI: 10.1109/ACCESS ...
Oct 24, 2022 · QuX. Statistics-enhanced direct batch growth self-organizing mapping for efficient DoS attack detection. IEEE Access. (2019). LeeJ.H. et al ...
Qu, Statistics-enhanced direct batch growth self-organizing mapping for efficient dos attack detection, IEEE Access, № 7, с. 78434 https://doi.org/10.1109 ...
Direct Batch Growth Hierarchical Self-Organizing Mapping Based on Statistics for Efficient Network Intrusion Detection.
Missing: Enhanced DoS Attack
Self-Organizing Map (SOM) which is an unsupervised artificial neural network. For detection, SOM firstly is trained with statistical features of network traffic ...
Missing: Direct Batch