Header: christian-rossow.de
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If you can't explain it simply, you don't understand it well enough.

Report - Paper 'Prudent Practices for Designing Malware Experiments: Status Quo and Outlook' accepted at IEEE S&P 2012

In this paper we explore issues relating to prudent experimental evaluation for projects that use malware-execution datasets. Our interest in the topic arose while analyzing malware and researching detection approaches ourselves, during which we discovered that well-working lab experiments could perform much worse in real-world evaluations. Investigating these difficulties led us to identify and explore the pitfalls that caused them. For example, we observed that even a slight artifact in a malware dataset can inadvertently lead to unforeseen performance degradation in practice. We summarized our paper as follows:

Malware researchers rely on the observation of malicious code in execution to collect datasets for a wide array of experiments, including generation of detection models, study of longitudinal behavior, and validation of prior research. For such research to reflect prudent science, the work needs to address a number of concerns relating to the correct and representative use of the datasets, presentation of methodology in a fashion sufficiently transparent to enable reproducibility, and due consideration of the need not to harm others.

In this paper we study the methodological rigor and prudence in 36 academic publications from 2006 to 2011 that rely on malware execution. 40% of these papers appeared in the 6 highest-ranked academic security conferences. We find frequent shortcomings, including problematic assumptions regarding the use of execution-driven datasets (25% of the papers), absence of description of security precautions taken during experiments (71% of the articles), and oftentimes insufficient description of the experimental setup. Deficiencies occur in top-tier venues and elsewhere alike, highlighting a need for the community to improve its handling of malware datasets. In the hope of aiding authors, reviewers, and readers, we frame guidelines regarding transparency, realism, correctness, and safety for collecting and using malware datasets.

I will present our work at IEEE S&P in San Francisco on Monday, 21.05.2012 (05/21/2012). We will soon launch a website that will allow the community to discuss aspects of prudent malware experimentation. In particular, this website will ask experts like you for feedback on how we - as a community - can further strive towards prudent malware experiments. More here soon!