Threat stream data generator: creating the known unknowns for test and evaluation of visual analytics tools

ABSTRACT

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.

REFERENCES

• 1: National Visualization and Analytics Center website. http://nvac.pnl.gov
• 2: Visual Analytics Science and Technology Symposium contest website. http://www.cs.umd.edu/hcil/VASTcontest06/

INDEX TERMS

Primary Classification:
  D. Software
  D.2 SOFTWARE ENGINEERING
      D.2.5 Testing and Debugging
          Subjects: Testing tools (e.g., data generators, coverage testing)

General Terms:
Design, Human Factors, Measurement, Performance, Reliability, Standardization, Verification

Keywords:
data generator, threat, threat stream