UNVEILING THE OPEN SOURCE VISUALIZATION ENGINE FOR BUSY HACKERS

The way a human efficiently digests information varies from person-to-person. Scientific studies have shown that some individuals learn better through the presentation of visual/spatial information compared to simply reading text. Why then do vendors expect customers to consume presented data following only the written word method as opposed to advanced graphical representations of the data? We believe this approach is dated.

To help the neglected visually inclined masses, we decided to create a free and Open Source engine to remove the complexity of creating advanced data visualizations. The ultimate goal of the project was to allow for the visualization of any loosely related data without having to endlessly reformat that data. For the visual/spatial learners, the engine will interpret their own data, whether it be a simple or complex system, and present the results in a way that their brains can understand.

Learning, for visual-spatial learners, takes place all at once, with large chunks of information grasped in intuitive leaps, rather than in the gradual accretion of isolated facts or small steps. For example, a visual-spatial learner can grasp all of the multiplication facts as a related set in a chart much easier and faster than memorizing each fact independently. We believe that some security practitioners might be able to better utilize their respective data sets if provided with an investigative model that their brains can understand.

During this presentation, we will show you how you can take any relational data set, quickly massage the format, and visualize the results. We will also share some observations and conclusions drawn from the results of the visualization that may not have appeared in simple text form. We have used this engine within OpenDNS to track CryptoLocker and CryptoDefense ransomware, Red October malware, and the Kelihos botnet. Additionally, specific Syrian Electronic Army (SEA) campaigns, carding sites, and even a map of the Internet via Autonomous Systems have been visualized using the engine.

Interesting data can also be isolated through the use of Python and JavaScript-based plugins that can be easily added to the engine's framework. These plugins affect the way the data is visualized and allow analysts to make sense of their data as it relates to the question they're trying to answer. The "big picture" model will help visually inclined incident responders, security analysts, and malware researchers visually stitch together complex data sets without needing a PhD in math or particle physics.

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