Researchers Develop Detection Method to Protect Army Networks

Researchers at the U.S. Army Combat Capabilities Development Command's Army Research Laboratory, working with colleagues at the University of Notre Dame and Purdue University. have developed a novel algorithm that can protect networks by detecting suspicious activity missed by current analytical methods.

Their goal was to build a higher-order network capable of identifying subtle changes in a stream of data that could indicate suspicious activity.

The researchers developed a high-order network representation, BuildHON+, reflecting real-world phenomena and scales for big data and existing network analysis tools, to perform network analytics.

Said the laboratory's Lance Kaplan, "Using a large-scale synthetic taxi movement data with 11 billion taxi movements, we show how multiple existing anomaly detection methods that depend on first-order network collectively fail to capture anomalous navigation behaviors beyond first-order, and how BuildHON+ can solve the problem."

The study was a collaboration with researchers

From "Researchers Develop Detection Method to Protect Army Networks"

U.S. Army Research Laboratory (08/17/20)
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