A hybrid model for classifying malware based on ResNet and Transformer
Author:
Affiliation:
1. Information Engineering University, China
Publisher
ACM
Link
https://dl.acm.org/doi/pdf/10.1145/3640912.3640958
Reference20 articles.
1. Ahmadi M. Ulyanov D. Semenov S. Trofimov M. and Giacinto G. 2016. Novel Feature Extraction Selection and Fusion for Effective Malware Family Classification. ACM. 2016. DOI:https://doi.org/10.1145/2857705.2857713.
2. Data augmentation based malware detection using convolutional neural networks
3. CruParamer: Learning on Parameter-Augmented API Sequences for Malware Detection
4. Dynamic Analysis for IoT Malware Detection With Convolution Neural Network Model
5. A novel framework for image-based malware detection with a deep neural network
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1. ResNet and Transformer Hybrid Malware Classification Model Based on Ensemble Learning;Proceedings of the 2023 7th International Conference on Electronic Information Technology and Computer Engineering;2023-10-20
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