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Proceedings Paper

Software analysis in the semantic web
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Paper Abstract

Many approaches in software analysis, particularly dynamic malware analyis, benefit greatly from the use of linked data and other Semantic Web technology. In this paper, we describe AIS, Inc.’s Semantic Extractor (SemEx) component from the Malware Analysis and Attribution through Genetic Information (MAAGI) effort, funded under DARPA’s Cyber Genome program. The SemEx generates OWL-based semantic models of high and low level behaviors in malware samples from system call traces generated by AIS’s introspective hypervisor, IntroVirtTM. Within MAAGI, these semantic models were used by modules that cluster malware samples by functionality, and construct “genealogical” malware lineages. Herein, we describe the design, implementation, and use of the SemEx, as well as the C2DB, an OWL ontology used for representing software behavior and cyber-environments.

Paper Details

Date Published: 28 May 2013
PDF: 8 pages
Proc. SPIE 8757, Cyber Sensing 2013, 87570A (28 May 2013); doi: 10.1117/12.2016122
Show Author Affiliations
Joshua Taylor, Assured Information Security, Inc. (United States)
Robert T. Hall, Assured Information Security, Inc. (United States)

Published in SPIE Proceedings Vol. 8757:
Cyber Sensing 2013
Igor V. Ternovskiy; Peter Chin, Editor(s)

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