Cybersecurity analysts deal with a huge amount of data, especially when monitoring network traffic. When printed in text form, network traffic in one day can be like a thick phone book. In other words, finding an anomaly is like looking for a needle in a haystack.
“This is an ocean of data,” says Yang Tsai, senior fellow at CyLab, in an interview with Carnegie Mellon University. “The important patterns that are important for us to see are hidden under a lot of trivial or normal patterns.”
Tsai has worked for years to find ways to make it easier to detect anomalies in network traffic. Several years ago, he and his research team developed a data visualization tool that allows you to perceive patterns of network traffic visually. Now the scientist has developed a way to hear them.
In a new study presented this week at the Applied Human Factors and Ergonomics Conference, Yang Tsai and two co-authors showed how cybersecurity data can be heard in the form of music. When the network traffic changes, so does the melody.
Tsai’s two research co-authors are professional musicians – Yakub Polachik and Caitlin Croft were once students of the College of Fine Arts at Carnegie Mellon University.
“We planned to learn how to find anomalies in network data, transforming them into a musical form. Using sound to perceive information is not a new practice, but so far there have not been solutions similar to ours in the world, ”noted Yang Tsai, adding that CyLab specialists had to experiment with different data transformation algorithms before getting the result.