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MAECO-Lite: Modular Ontology for Dynamic Malware Analysis

A lightweight ontology designed to represent data and operationalize its processing for dynamic malware analysis.

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MAECO-Lite: Modular Ontology for Dynamic Malware Analysis

By Zekeri Adams, Peter Švec, Ján Kľuka, Roderik Ploszek, Monday Onoja, Štefan Balogh, Martin HomolaarXiv
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The paper proposes MAECO-Lite, a modular ontology that separates enduring entities from runtime events. It is based on an ontological analysis of core MAEC constructs relevant to dynamic malware analysis. The ontology improves learning performance using description logic concept learning algorithms.

Abstract

The paper proposes MAECO-Lite, a modular ontology that separates enduring entities from runtime events. It is based on an ontological analysis of core MAEC constructs relevant to dynamic malware analysis. The ontology improves learning performance using description logic concept learning algorithms.

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malware-analysisdynamic-behaviorontology-designsemanticsdata-representationOntology & TaxonomySemantic InteroperabilityContent OperationsKnowledge Graphs
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