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This paper surveys various log clustering approaches for cyber security applications, highlighting their applicability, limitations, and trends. It categorizes existing methods based on their clustering techniques and objectives, such as anomaly detection and signature extraction. The authors propose a decision model to assist users in selecting appropriate clustering methods tailored to their specific requirements.

Author

vishruti

Language

EN