Measurement of Malware Family Classification on a Large-Scale Real-World Dataset
Author:
Affiliation:
1. Institute of Information Engineering,Chinese Academy of Sciences,Beijing,China
2. Coordination Center of China,National Computer Network Emergency Response Technical Team,Beijing,China
3. Beijing Chaitin Technology Co.,Ltd,Beijing,China
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10063338/10063342/10063492.pdf?arnumber=10063492
Reference32 articles.
1. A Multi-Dimensional Deep Learning Framework for IoT Malware Classification and Family Attribution
2. Binary File’s Visualization and Entropy Features Analysis Combined with Multiple Deep Learning Networks for Malware Classification
3. A Novel Malware Detection and Family Classification Scheme for IoT Based on DEAM and DenseNet
4. MalFCS: An effective malware classification framework with automated feature extraction based on deep convolutional neural networks
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