Vigilants Electromagnetic Battle Damage Assessment Toolkit (EMBDAT) is designed to assess the effects of HPEM attack using data from multiple sensors and to ascertain the utility of each sensor toward the battle damage assessment. It provides tools for modeling the target system, HPEM weapon, and sensors used in an engagement. It integrates with various sensors and uses statistical analysis techniques and machine learning analytics to assess the state of the target system during and after an HPEM attack. EMBDAT integrates with our Toolkit for Assessing Electromagnetic Disruption Recovery (TAEMDR), which performs EM attack simulations that are used to train the EMBDAT classifiers. EMBDAT then utilizes classifier transformations to allow the trained classifiers to generalize to operate on different system and sensor configurations. During an HPEM attack and subsequent recovery, EMBDAT analytics run in real-time to provide the user continuous updates on the status of the target and the estimated time until it returns to normal operation. To support the EMBDAT development, we are investigating sensing techniques including active and passive cyber sensors as well as sensors based on side channel attacks.
