Accuracy (10-fold): 0.9976Macro F1 (10-fold): 0.9931
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Malware Classification
Malware Classification is the process of assigning a malware sample to a specific malware family. Malware within a family shares similar properties that can be used to create signatures for detection and classification. Signatures can be categorized as static or dynamic based on how they are extracted. A static signature can be based on a byte-code sequence, binary assembly instruction, or an imported Dynamic Link Library (DLL). Dynamic signatures can be based on file system activities, terminal commands, network communications, or function and system call sequences.
<span class="description-source">Source: Behavioral Malware Classification using Convolutional Recurrent Neural Networks </span>
논문
Accuracy (10-fold): 0.9913LogLoss: 0.0419Macro F1 (10-fold): 0.9830
Accuracy (10-fold): 0.9894LogLoss: 0.367724Macro F1 (10-fold): 0.9813
Accuracy (10-fold): 0.9924Macro F1 (10-fold): 0.9872
Accuracy: 0.8492
Accuracy (10-fold): 0.9848Macro F1 (10-fold): 0.9580
Accuracy (10-fold): 0.9861LogLoss: 0.106343Macro F1 (10-fold): 0.9719
Accuracy (10-fold): 0.9917LogLoss: 0.0244Macro F1 (10-fold): 0.9856
Accuracy: 0.985Macro F1: 0.9391
Accuracy (5-fold): 98.94
Accuracy (10-fold): 0.9912LogLoss: 0.0431Macro F1 (10-fold): 0.9908