Understanding of Multi-Source Wireless RF Network Structures

Adversary networks are robust, diverse, and observable only during the limited time periods they exist. Valuable intelligence information can be extracted from exploitation of these networks, especially via correlating activities across these short-lived networks. Cross network correlation can potentially satisfy existing operational requirements. The RF Network Understanding System (RFNUS) is focused on delivering operational intelligence by applying unique cross network exploitation and correlation techniques. The Phase I activity demonstrated the feasibility of this approach. The Phase II effort will expand the Phase I concept in three major areas. First, the number and types of networks targeted will be expanded to include exploitation of collection from current collection sensors and associated data sources. Second, the system will take advantage of classified information available from those sensors including expanded external information (including header data, and currently unavailable parameters such as power and geolocation data. Finally, with the addition of more networks and more data from those networks, the logic contained within the discovery tool will be expanded to fully exploit the wider range of target data. Ultimately, the Phase II objective is to produce a deployable prototype system for field testing. The prototype will be developed by identifying requirements collaboratively with the customer, and executing a workplan consisting of design, development, and integration and test tasks.