"Professor Receives Grant as Part of $14 Million Industry Collaboration to Improve Secure Communications"
The Intelligence Advanced Research Projects Activity (IARPA) has awarded a $14 million contract to fund a collaborative project between BAE Systems and a team of researchers at Virginia Tech in order to meet the growing demand for secure communications research and development. The award aims to create tools for deciphering an ever-increasing number of radio frequency signals to quickly and accurately help secure mission-critical information. The Virginia Tech team will provide expertise in Machine Learning (ML)-based strategies for radio frequency anomaly detection. The team will focus on reservoir computing, a type of computing used to predict a network's activity and occupancy based on observations of a small sample piece of that network. When it comes to secure communications, looking at a small section to predict activity on a larger scale is especially important because analyzing the entire network in a time-sensitive situation would be nearly impossible. As information travels quickly, threats can cause widespread damage in seconds. It is critical to be able to identify a threat as soon as possible in order to prevent damage on a large scale. Signal characterization will also be used by the team to identify the types of signals being sent within the secure communications network. The hope is that the technology developed using these prediction and characterization techniques will improve situational awareness, help target threats, and secure communications against malicious attacks. BAE Systems will provide suggestions and guidance to the team on setting up the experiment. This assistance includes providing a baseline of simulated data before moving on to actual hardware testbed data. The advanced defense technology company will then collaborate with the Virginia Tech team to review the success of the proposed candidate technologies, including how well they work to analyze anomalies and threats, and provide suggestions and feedback based on those test runs. This article continues to discuss the collaborative project aimed at improving secure communications.