2022
DOI: 10.1007/978-3-031-08530-7_45
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Malware Classification Based on Graph Convolutional Neural Networks and Static Call Graph Features

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Cited by 2 publications
(4 citation statements)
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“…A multitude of research papers are presented from the past decade, and it is clearly shown that one particular feature is by far the most frequently used in this domain -the static call graph. Our previous work [17] presents a detailed overview on the literature of PE analysis, based on this survey paper, visualizing the distribution of research work with histograms of the features and methods applied. The motivation to use one particularly interesting static feature, the call graph, is that it includes both topological information of an executable file regarding function call sequences, and also the x86 assembly instruction list of each local subroutine -one presumption of the analysis process is that each of these local subroutines may be an original code of a malicious actor or APT group.…”
Section: Related Workmentioning
confidence: 99%
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“…A multitude of research papers are presented from the past decade, and it is clearly shown that one particular feature is by far the most frequently used in this domain -the static call graph. Our previous work [17] presents a detailed overview on the literature of PE analysis, based on this survey paper, visualizing the distribution of research work with histograms of the features and methods applied. The motivation to use one particularly interesting static feature, the call graph, is that it includes both topological information of an executable file regarding function call sequences, and also the x86 assembly instruction list of each local subroutine -one presumption of the analysis process is that each of these local subroutines may be an original code of a malicious actor or APT group.…”
Section: Related Workmentioning
confidence: 99%
“…In order to obtain the assembly code of each subroutine, "agf" command is called on each node of the call graph. In a similar manner to generating the call graph using IDA Pro 6, merging the output of "GenCallGdl" and "GenFuncGdl" [17,18,19], the same logic applies in Radare2 as well. Both the global function graph ("agC") and global references graph ("agR") is needed to be analyzed, furthermore, each function block ("agf") must be processed in order to obtain the final, complete call graph.…”
Section: 3mentioning
confidence: 99%
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