MAECO-Lite: Modular Ontology for Dynamic Malware Analysis 文章

ArXiv CS.AI2026-06-01NEWSen作者: Zekeri Adams, Peter \v{S}vec, J\'an K\v{l}uka, Roderik Ploszek, Monday Onoja, \v{S}tefan Balogh, Martin Homola

摘要

arXiv:2605.31199v1 Announce Type: cross Abstract: Capturing dynamic malware behavior in a practical but still semantically precise manner remains a significant challenge in cyber threat intelligence. While standards such as MAEC and STIX provide widely adopted vocabularies for describing malware artifacts and observations, they represent data with considerable complexity in structures that often obscure important ontological distinctions. In particular, they tend to conflate enduring malware artifacts with the events generated during execution, thereby flattening distinctions that are central in foundational standards for ontology design. In this paper, we conduct a foundational ontological analysis of core MAEC and STIX constructs relevant to dynamic malware analysis relying on Unified Foundational Ontology (UFO) as a theoretical lens.

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MAECO-Lite: Modular Ontology for Dynamic Malware Analysis
2026-06-01PRODUCT_LAUNCH影响: MEDIUM

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