Computer Science > Cryptography and Security
[Submitted on 19 Dec 2016 (v1), last revised 24 Feb 2017 (this version, v3)]
Title:A Knowledge-Assisted Visual Malware Analysis System: Design, Validation, and Reflection of KAMAS
View PDFAbstract: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 work flow-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.
Submission history
From: Alexander Rind [view email][v1] Mon, 19 Dec 2016 15:48:48 UTC (3,426 KB)
[v2] Thu, 22 Dec 2016 12:23:08 UTC (3,426 KB)
[v3] Fri, 24 Feb 2017 10:10:28 UTC (2,279 KB)
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