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Analysis of cyber relevant data has become an area of increasing focus. Aslarger percentages of businesses and governments begin to understand theimplications of cyberattacks, the impetus for better cybersecurity solutionshas increased. Unfortunately, current cybersecurity datasets either offer noground truth or do so with anonymized data. The former leads to a quandary whenverifying results and the latter can remove valuable information. Additionally,most existing datasets are large enough to make them unwieldy during prototypedevelopment. In this paper we have developed the PicoDomain dataset, a compacthigh-fidelity collection of Zeek logs from a realistic intrusion using relevantTools, Techniques, and Procedures. While simulated on a small-scale network,this dataset consists of traffic typical of an enterprise network, which can beutilized for rapid validation and iterative development of analytics platforms.We have validated this dataset using traditional statistical analysis andoff-the-shelf Machine Learning techniques.

PicoDomain: A Compact High-Fidelity Cybersecurity Dataset