Enhancing network security with information-guided-enhanced Runge Kutta feature selection for intrusion detection

Intrusion detection system (IDS) classify network traffic as either threatening or normal based on data features, aiming to identify malicious activities attempting to compromise computer systems. However, the volume of intrusion-related data is increasing daily, and the redundant features within th...

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Veröffentlicht in:	Cluster computing 2024-12, Vol.27 (9), p.12569-12602
Hauptverfasser:	Yuan, Li, Tian, Xiongjun, Yuan, Jiacheng, zhang, Jingyu, Dai, Xiaojing, Heidari, Ali Asghar, Chen, Huiling, Yu, Sudan
Format:	Artikel
Sprache:	eng
Schlagworte:	Accuracy Algorithms Artificial intelligence Communication Communications traffic Computer Communication Networks Computer Science Datasets Feature selection Heuristic Internet of Things Intrusion detection systems Machine learning Methods Neural networks Operating Systems Optimization algorithms Processor Architectures Runge-Kutta method
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