Article

Classifier-Guided Discrete Diffusion for Malware Family-Conditional Graph Generation

2026-04-24

Abstract excerpt

<title>Abstract</title> <p>We study whether discrete graph diffusion can be adapted to generate directed, weighted malware API call transition graphs in the low-data regime typical of dynamic malware analysis. Each execution trace is converted into a behavior graph whose nodes represent API types and whose directed edges represent transition count frequencies. We adapt a graph generative model, DiGress, to this s...

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Literature Corpus work: 9b090b24-aa40-587c-a733-f494047ed255
DOI: 10.21203/rs.3.rs-9226468/v1

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