Alert correlation is a system that receives alerts from heterogeneous Intrusion Detection Systems and reduces false alerts, detects high-level patterns of attacks, increases the meaning of occurred incidents, predicts the future states of attacks, and detects root cause of attacks. This paper presents self-organizing maps and the k-means machine learning algorithms to reduce the number of alerts by clustering them.
CITATION STYLE
Ambawade, D., & Bakal, Dr. J. W. (2022). Alert Clustering using Self-Organizing Maps and K-Means Algorithm. International Journal of Engineering and Advanced Technology, 12(1), 82–87. https://doi.org/10.35940/ijeat.a3852.1012122
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