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In order to assure accuracy and realism of resilience assessment methods and tools, it is essential to have access to field data that are unbiased and representative. Several initiatives are taking place that offer access to malware samples for research purposes. Papers are published where techniques have been assessed thanks to these samples. Definition of benchmarking datasets is the next step ahead. In this paper, the authors report on the lessons learned while collecting and analyzing malware samples in a large scale collaborative effort. Three different environments are described and their integration used to highlight the open issues that remain with such data collection. Three main lessons are offered to the reader.
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