Similarity-Based Malware Classification Using Graph Neural Networks

Similarity-Based Malware Classification Using Graph Neural Networks

This work proposes a novel malware identification model that is based on a graph neural network (GNN). The function call relationship and function assembly content obtained by analyzing the malware are used to generate a graph that represents the functional structure of a malware sample. In addition...

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Bibliographic Details
Main Authors: Yu-Hung Chen, Jiann-Liang Chen, Ren-Feng Deng
Format: Article
Language:English
Published: MDPI AG 2022-10-01
Series:Applied Sciences
Subjects:
malware families
classification
similarity
graph neural networks
Siamese network
Malware Bazaar dataset
Online Access:https://www.mdpi.com/2076-3417/12/21/10837

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