Titel (eng): Video Walkthrough of KAMAS

Autor: Wagner, M. (Markus)
Rind, A. (Alexander)
Thür, N. (Niklas)
Aigner, W. (Wolfgang)

Beschreibung (eng): IT-security experts engage in behavior-based malware analysis in order to learn about previously unknown samples of malicious software
(malware) or malware families. For this, they need to find and categorize suspicious patterns from large collections of execution traces. Currently available systems do not meet the analysts' needs described as: visual access suitable for complex data structures, visual representations appropriate for IT-security experts, provide workflow-specific interaction techniques, and the ability to externalize knowledge in the form of rules to ease analysis and for sharing with colleagues. To close this gap, we designed and developed KAMAS, a knowledge-assisted visualization system for behavior-based malware analysis. KAMAS supports malware analysts with visual analytics and knowledge externalization methods for the analysis process. The paper at hand is a design study that describes the design, implementation, and evaluation of the prototype. We report on the validation of KAMAS by expert reviews, a user study with domain experts, and focus group meetings with analysts from industry. Additionally, we reflect the gained insights of the design study and discuss the advantages and disadvantages of the applied visualization methods. It is very interesting that the arc-diagram was one of the preferred visualization techniques during the design phase but it did not provide the expected benefits for pattern finding. In contrast, the seemingly simple looking connection line was described as supportive finding the link between these tables.

Sprache des Objekts: Englisch

Datum: 2017

Rechte: © Alle Rechte vorbehalten

Klassifikation: malicious software; malware analysis; behavior-based; prototype; visualization; visual analytics; interactive; knowledge generation; design study

Mitglied in der/den Collection(s) (2):
o:1928 KAVAGait: Knowledge-Assisted Visual Analytics for Clinical Gait Analysis
o:1264 A knowledge-assisted visual malware analysis system: Design, validation and reflection of KAMAS
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