Automated Detection Of Network Intrusions Using Machine Learning in Real-Time Systems

Aulia Novi
Ryan Satria

International Journal of Computer Technology and Science
Vol. 1 No. 2 (2024): April : International Journal of Computer Technology and Science

Network intrusion detection is crucial for maintaining the integrity of real-time systems. This paper evaluates various machine learning algorithms, including support vector machines (SVM) and decision trees, for real-time intrusion detection. Through extensive testing on simulated datasets, the study highlights the advantages of automated detection in reducing response times and enhancing network security.