We study techniques to visualize the behavior of malicious software (malware). Our aim is to help human analysts to quickly assess and classify the nature of a new malware sample. Our techniques are based on a parametrized abstraction of detailed behavioral reports automatically generated by sandbox environments. We then explore two visualization techniques: treemaps and thread graphs. We argue that both techniques can effectively support a human analyst (a) in detecting maliciousness of software, and (b) in classifying malicious behavior.
In contrast to the data published by Payne and Huntsman in 1982, no association between GLO I and Hp phenotypes could be found in a sample of 973 unrelated Austrians.
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