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Found 4 papers, 0 papers with code
Decision-forest voting scheme for classification of rare classes in network intrusion detection
The algorithm leverages out-of-bag datasets to estimate prediction errors of individual trees, which are then used in accordance with the Bayes rule to refine the decision of the ensemble.
Joint Detection of Malicious Domains and Infected Clients
Detection of malware-infected computers and detection of malicious web domains based on their encrypted HTTPS traffic are challenging problems, because only addresses, timestamps, and data volumes are observable.
Bad practices in evaluation methodology relevant to class-imbalanced problems
For research to go in the right direction, it is essential to be able to compare and quantify performance of different algorithms focused on the same problem.
Learning detectors of malicious web requests for intrusion detection in network traffic
This paper proposes a generic classification system designed to detect security threats based on the behavior of malware samples.
