… intrusion detection system achieves the detection with better … NIDS using data mining
and five types of agents based on … a multi-class problem of intrusion detection using multi-agent …

… is a main enhanced algorithm, Snort-based IPS. DDoS attack … create an intrusion detection
system to detect DDoS attacks. … attack detection is usually regarded as a binary or multiclass …

… area existing of intrusion detection systems that use big data … Support Vector Machine,
Random Forest, and Decision Tree, … , since the intrusion detection rate is increased and the false …

… in intrusions detection, the survey also discussed agent based IDS, … based on an improved
Bully algorithm for timely system … an algorithm based on Support Vector Machine (SVM) for …

… show that our proposed system improved the Recall, Accuracy, … SVM algorithms are a good
candidate for intrusion detection. … It can be shown that each multi-class problem can be easily …

… intrusion detection system achieves the detection with better … NIDS using data mining
and five types of agents based on … a multi-class problem of intrusion detection using multi-agent …

… SVM, clustering methods, and a simple feature selection … When studying intrusion detection
in multiclass, the recall … a robust reinforcement learning model, enhancing the model’s …

… novel multi-agentbased design to enhance the cyber resilience … -based intrusion detection
solution based on a Multi-Agent … tree-based multiclass support vector machines (DTSVM) are …

… power of artificial intelligence to anomaly detection. However, … comparison with SVM and
RF, ELM performs better in terms … attention values for the agents based on the context. The …

… are detected in cyber security by using ML techniques like SVM, … framework increased the
intrusion detection in cyber security, … of attacks; the multi-class classification model was used in …