← Malware Classification
Papers with Code · CC BY-SA 4.0

Microsoft Malware Classification Challenge

아카이브 평가 29건 · 마지막 적재/변경

평가 기록

과거 수집 기록이며 최신 순위가 아닙니다. 데이터셋 버전·split·실험 조건과 지표 방향이 검증되지 않은 결과는 직접 비교할 수 없습니다. 날짜는 논문 날짜이며 최신 평가일을 뜻하지 않습니다.

표가 화면보다 넓으면 좌우로 스크롤하여 논문과 구현 링크를 확인하세요.

원본 기록 순서 · 순위 미부여
모델원본 지표·값논문구현
Ahmadi et al. (2016): ENT, Bytes 1-G, STR, IMG1, IMG2, MD1, MISC, OPC, SEC, REG, DP, API, SYM, MD2 IMG and Opcode N-Grams + Ensemble Learning (XGBoost)
Accuracy (10-fold)
0.9976
Macro F1 (10-fold)
0.9931
HYDRA: A multimodal deep learning framework for malware classification
2020-05-12
코드 1
HYDRA
Accuracy (10-fold)
0.9975
Macro F1 (10-fold)
0.9951
HYDRA: A multimodal deep learning framework for malware classification
2020-05-12
코드 1
Zhang et al. (2016): Total lines of each Section, Operation Code Count, API Usage, Special Symbols Count, Asm File Pixel Intensity Feature, Bytes File Block Size Distribution, Bytes File N-Gram + Ensemble Learning (XGBoost)
Accuracy (10-fold)
0.9974
Macro F1 (10-fold)
0.9938
HYDRA: A multimodal deep learning framework for malware classification
2020-05-12
코드 1
Orthrus
Accuracy (10-fold)
0.9924
Macro F1 (10-fold)
0.9872
Orthrus: A Bimodal Learning Architecture for Malware Classification
2020-09-28
코드 1
Opcode-based Shallow CNN
Accuracy (10-fold)
0.9917
LogLoss
0.0244
Macro F1 (10-fold)
0.9856
Convolutional Neural Network for Classification of Malware Assembly Code
2017-10-27
코드 1
Hierarchical Convolutional Network
Accuracy (10-fold)
0.9913
LogLoss
0.0419
Macro F1 (10-fold)
0.9830
A Hierarchical Convolutional Neural Network for Malware Classification
2019-09-30
연결 없음
SEA
Accuracy (10-fold)
0.9912
LogLoss
0.0431
Macro F1 (10-fold)
0.9908
Sequential Embedding-based Attentive (SEA) classifier for malware classification
2023-02-11
코드 1
Dynamic Time Wrapping + K-NN
Accuracy (10-fold)
0.9894
LogLoss
0.367724
Macro F1 (10-fold)
0.9813
Classification of Malware by Using Structural Entropy on Convolutional Neural Networks
2018-04-27
코드 1
Ahmadi et al. (2016): API feature vector + XGBoost
Accuracy (10-fold)
0.9868
Macro F1 (10-fold)
0.9638
HYDRA: A multimodal deep learning framework for malware classification
2020-05-12
코드 1
Autoencoders+Residual Network
Accuracy (10-fold)
0.9861
LogLoss
0.106343
Macro F1 (10-fold)
0.9719
An End-to-End Deep Learning Architecture for Classification of Malware’s Binary Content
2018-09-27
연결 없음
Multiresolution CNN
Accuracy (10-fold)
0.9828
LogLoss
0.124431
Macro F1 (10-fold)
0.9636
Classification of Malware by Using Structural Entropy on Convolutional Neural Networks
2018-04-27
코드 1
CNN+BiLSTM
Accuracy (10-fold)
0.9820
LogLoss
0.0744
Macro F1 (10-fold)
0.9605
A Hierarchical Convolutional Neural Network for Malware Classification
2019-09-30
연결 없음
Scaled bytes sequence + CNN & Bidirectional LSTM
Accuracy (10-fold)
0.9814
Macro F1 (10-fold)
0.9662
HYDRA: A multimodal deep learning framework for malware classification
2020-05-12
코드 1
Grayscale images + Opcode N-grams (Feature selection for malware classification)
Accuracy (10-fold)
0.9770
Orthrus: A Bimodal Learning Architecture for Malware Classification
2020-09-28
코드 1
DeepConv
Accuracy (10-fold)
0.9756
LogLoss
0.1602
Macro F1 (10-fold)
0.9071
A Hierarchical Convolutional Neural Network for Malware Classification
2019-09-30
연결 없음
Gray-scale IMG CNN
Accuracy (10-fold)
0.9750
LogLoss
0.184483
Macro F1 (10-fold)
0.9400
Accuracy (5-fold)
0.973
Using Convolutional Neural Networks for Classification of Malware represented as Images
2018-08-27
코드 1
Hierarchical Attention Network
Accuracy (10-fold)
0.9742
LogLoss
0.0933
Macro F1 (10-fold)
0.9468
A Hierarchical Convolutional Neural Network for Malware Classification
2019-09-30
연결 없음
Structural entropy CNN
Accuracy (10-fold)
0.9708
LogLoss
0.134624
Macro F1 (10-fold)
0.9314
Classification of Malware by Using Structural Entropy on Convolutional Neural Networks
2018-04-27
코드 1
Narayanan et al. (2016): PCA features + 1-NN
Accuracy (10-fold)
0.9660
Macro F1 (10-fold)
0.9102
HYDRA: A multimodal deep learning framework for malware classification
2020-05-12
코드 1
Deep Transferred Generative Adversarial Networks
Accuracy (10-fold)
0.9639
Orthrus: A Bimodal Learning Architecture for Malware Classification
2020-09-28
코드 1
Zero Rule Classifier
Accuracy (10-fold)
0.2707
HYDRA: A multimodal deep learning framework for malware classification
2020-05-12
코드 1
Random Guess Classifier
Accuracy (10-fold)
0.1755
HYDRA: A multimodal deep learning framework for malware classification
2020-05-12
코드 1
Multiresolution CNN + Bagging
LogLoss
0.075081
Classification of Malware by Using Structural Entropy on Convolutional Neural Networks
2018-04-27
코드 1
MalConv
Accuracy (10-fold)
0,9641
LogLoss
0.3071
Macro F1 (10-fold)
0.8902
A Hierarchical Convolutional Neural Network for Malware Classification
2019-09-30
연결 없음
TPOT Classifier
Accuracy (5-fold)
98.94
Malware Classification Using Static Disassembly and Machine Learning
2021-12-10
코드 1 · 코드 2
CNN BiLSTM - Reb Sampl
Accuracy (5-fold)
98.20
F1 score (5-fold)
96.05
Deep learning at the shallow end: Malware classification for non-domain experts
2018-07-22
코드 1
Haralick features + XGBoost
Accuracy (5-fold)
0.9550
Using Convolutional Neural Networks for Classification of Malware represented as Images
2018-08-27
코드 1
LBP features + XGBoost
Accuracy (5-fold)
0.951
Using Convolutional Neural Networks for Classification of Malware represented as Images
2018-08-27
코드 1
GA Designed Deep CNN
Accuracy
0.9307
Designing Deep Convolutional Neural Networks using a Genetic Algorithm for Image-based Malware Classification
2022-07-18
연결 없음