arXiv:2609.38390v1 Announce Type: new Abstract: Effective malware analysis requires understanding not only whether a program is malicious, but also which behaviors it exhibits and where those behaviors originate in the code. Existing machine-learning-based malware detectors largely operate as black boxes, providing limited insight into the malicious logic responsible for their decisions.
Behavior-Centric Malware Classification with Fine-Grained Malicious Logic Localization
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