HyperAI
الرئيسيةالأخبارأحدث الأوراق البحثيةالدروسمجموعات البياناتالموسوعةSOTAنماذج LLMلوحة الأداء GPUالفعاليات
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HyperAI

Malware Classification On Microsoft Malware

المقاييس

Accuracy (10-fold)

النتائج

نتائج أداء النماذج المختلفة على هذا المعيار القياسي

اسم النموذج
Accuracy (10-fold)
Paper TitleRepository
Grayscale images + Opcode N-grams (Feature selection for malware classification)0.9770Orthrus: A Bimodal Learning Architecture for Malware Classification
Ahmadi et al. (2016): API feature vector + XGBoost0.9868HYDRA: A multimodal deep learning framework for malware classification
Structural entropy CNN0.9708Classification of Malware by Using Structural Entropy on Convolutional Neural Networks
CNN+BiLSTM0.9820A Hierarchical Convolutional Neural Network for Malware Classification-
LBP features + XGBoost-Using Convolutional Neural Networks for Classification of Malware represented as Images
CNN BiLSTM - Reb Sampl-Deep learning at the shallow end: Malware classification for non-domain experts
Hierarchical Attention Network0.9742A Hierarchical Convolutional Neural Network for Malware Classification-
Scaled bytes sequence + CNN & Bidirectional LSTM0.9814HYDRA: A multimodal deep learning framework for malware classification
Opcode-based Shallow CNN0.9917Convolutional Neural Network for Classification of Malware Assembly Code
Haralick features + XGBoost-Using Convolutional Neural Networks for Classification of Malware represented as Images
MalConv0,9641A Hierarchical Convolutional Neural Network for Malware Classification-
Deep Transferred Generative Adversarial Networks0.9639Orthrus: A Bimodal Learning Architecture for Malware Classification
SEA0.9912Sequential Embedding-based Attentive (SEA) classifier for malware classification
Zero Rule Classifier0.2707HYDRA: A multimodal deep learning framework for malware classification
Orthrus0.9924Orthrus: A Bimodal Learning Architecture for Malware Classification
Multiresolution CNN0.9828Classification of Malware by Using Structural Entropy on Convolutional Neural Networks
Gray-scale IMG CNN0.9750Using Convolutional Neural Networks for Classification of Malware represented as Images
Random Guess Classifier0.1755HYDRA: A multimodal deep learning framework for malware classification
Narayanan et al. (2016): PCA features + 1-NN0.9660HYDRA: A multimodal deep learning framework for malware classification
Autoencoders+Residual Network0.9861An End-to-End Deep Learning Architecture for Classification of Malware’s Binary Content-
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