AUC: 0.94
Papers with Code · CC BY-SA 4.0
Intrusion Detection
Intrusion Detection is the process of dynamically monitoring events occurring in a computer system or network, analyzing them for signs of possible incidents and often interdicting the unauthorized access. This is typically accomplished by automatically collecting information from a variety of systems and network sources, and then analyzing the information for possible security problems.
<span class="description-source">Source: Machine Learning Techniques for Intrusion Detection </span>
논문
Avg F1: 0.94Recall: 99.7Precision: 88.7
Accuracy: 99.6Precision: 99.5Recall: 99.75
Accuracy (%): 98.07Precision (Macro Avg): 98.08Recall (Macro Avg): 98.07F1 Score (Macro Avg): 98.07
Actions Top-1 (S2): action
Avg F1: 0.9875Recall: 98.34Precision: 99.26
0..5sec: wwwwwwww
Average Class Accuracy: 98.85%
AUC: 0.969Average Precision: 0.883
Avg F1: 0.908Recall: 86.2Precision: 95.9
Accuracy: 93
F1 Score: 0.893
Synthesis of a Machine Learning Model for Detecting Computer Attacks Based on the CICIDS2017 Dataset
Avg F1: 0.971Recall: 96.1Precision: 98.2