Novel Battle Damage Assessment Using Sensor Networks

Vigilant Cyber Systems, Inc. proposed to design and develop the Electromagnetic Battle Damage Assessment Tool (EMBDAT) to assess the effects of high-power electromagnetic (HPEM) attack using sensor data from the system under attack (target system) and other known quantities about the target and weapon. It is designed to integrate with a variety of sensors and provides an application programming interface (API) through which new sensors can be added. Further, it provides machine learning analytics not only to assess the effects on the target, but also to quantify the contribution of each sensor to the damage assessment. To train these analyzers, EMBDAT provides a machine learning HPEM battle damage assessment (BDA) toolkit. This toolkit allows EMBDAT operators to train the analyzers using data from previous HPEM attacks and tests as well as simulated HPEM events.