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Carnegie Mellon Researchers Create Data Visualization Tool to Identify Cyber Attacks

Researchers at Carnegie Mellon University's CyLab Security and Privacy Institute have developed a new tool for analyzing network traffic and identifying cyber attacks. The tool uses data visualization to make it easier for network analysts to see key changes and patterns generated by distributed denial of service attacks, malware distribution networks and other malicious network traffic. 

"Lots of network traffic data is collected in the form of static reports, but it is very overwhelming for an analyst to digest those data," said Yang Cai, senior systems scientist and director CyLab's Visual Intelligence Studio, in a press release. "Visualization is one way to change abstract data into pictures, sound, and videos so you can see patterns in a very intuitive way."

"Based on these visualization graphs, analysts can focus on critical areas to help shut down a malware distribution network, or in the case of a DDoS attack, target a critical node to thwart the attack," noted Sebastian Peryt, a research assistant in CyLab. Cai and Peryt presented the tool last week at the IEEE Symposium on Visualization for Cybersecurity in Baltimore, MD.

The team plans to integrate the tool into a virtual reality platform "so analysts can more easily explore the graphs with intuitive motions," according to a CyLab statement. Future plans also include improvements to make the tool more user-friendly and operate more efficiently.

For more information, including a video demonstration of the tool, visit the CyLab site.

About the Author

Rhea Kelly is editor in chief for Campus Technology, THE Journal, and Spaces4Learning. She can be reached at [email protected].

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