Tyson Johnson Presents at ISS World OSINT Automation Training Seminar
On February 19, 2015, Tyson Johnson, BrightPlanet’s Vice President of Business Development, presented at ISS World’s training seminar on open source intelligence (OSINT) automation. ISS World’s one-day training seminar focused on using OSINT automation platforms for early warning protection against Internet-based security attacks.
In his presentation, Tyson gave tips for developing an OSINT platform for early warning detection. Tyson’s key takeaways were:
- Companies need to utilize OSINT
- Companies need to decide what they want the data to tell them
- Data input is equally as important as data output
Tyson began his presentation with discussion around utilizing open source intelligence, more commonly referred to as OSINT, to help in decision support. Through the use of harvesting and curating open source, unstructured content, practitioners and intelligence analysts no longer need to rely on internal data that may be lacking in depth and quality. They can utilize open sources such as the Internet for analysis and OSINT solutions.
Decide What You Want the Data to Tell You
The second point Tyson emphasized was ensure there is an agreed upon mission. Tyson explained that organizations need to be able to answer the question, “What is the objective of harvesting data so that we can make sense of the analytics?”
Often companies know they need access to a certain dataset and rush to get access to the data, but they don’t ask what they truly want out of the data after it’s collected. Having a predefined mission and objective for collecting the data will save time in the long run.
Data Collection is Important
The last point Tyson emphasized was that companies need to focus on data collection and curation. “Garbage in, equals garbage out; really horrible data leads makes nonsensical analytics. Focus on collection of data”, maintains Johnson while trying to explain the importance of ensuring that quality data goes into the system.
Making an emphasis on receiving robust quality data in an OSINT project will lead to more robust quality analytics. Without the proper data set to analyze and make sense of, the amount of analytics doesn’t matter at all.
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