📅 30 April 2024
DOI: 10.62951/ijcts.v1i2.63
Automated Detection Of Network Intrusions Using Machine Learning in Real-Time Systems
International Journal of Computer Technology and Science
Asosiasi Riset Teknik Elektro dan Informatika Indonesia (ARTEII)
📄 Abstract
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.
🔖 Keywords
#Intrusion detection; Real-time systems; Machine learning; Support vector machine; Network security; Decision tree
ℹ️ Informasi Publikasi
Tanggal Publikasi
30 April 2024
Volume / Nomor / Tahun
Volume 1, Nomor 2, Tahun 2024
📝 HOW TO CITE
Aulia Novi; Ryan Satria, "Automated Detection Of Network Intrusions Using Machine Learning in Real-Time Systems," International Journal of Computer Technology and Science, vol. 1, no. 2, Apr. 2024.
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