威胁流数据生成器:为可视化分析工具的测试和评估创建已知的未知

M. Whiting, W. Cowley, J. Haack, Douglas Love, S. Tratz, Carrie Varley, Kim Wiessner
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引用次数: 6

摘要

我们介绍了威胁流数据生成器,这是一种为可视化分析工具和环境的测试和评估创建合成数据集的方法和工具。我们专注于与信息分析师合作,以了解威胁数据的特征,开发允许我们定义具有已知基础事实的数据集的场景,定义将场景中的威胁元素映射到数据中的表达式的过程,并创建软件系统来生成数据。我们还在开发方法来评估我们的数据集,考虑到威胁的微妙性和要检查的软件的数据的适当性等特征。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Threat stream data generator: creating the known unknowns for test and evaluation of visual analytics tools
We present the Threat Stream Data Generator, an approach and tool for creating synthetic data sets for the test and evaluation of visual analytics tools and environments. We have focused on working with information analysts to understand the characteristics of threat data, to develop scenarios that will allow us to define data sets with known ground truth, to define a process of mapping threat elements in a scenario to expressions in data, and creating a software system to generate the data. We are also developing approaches to evaluating our data sets considering characteristics such as threat subtlety and appropriateness of data for the software to be examined.
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