► VIDEO | “Applying Deep Reinforcement Learning (DRL) in a Cyber Wargaming Engine”

► VIDEO | March 19th, 2021 | 12:00pm – 1:00pm EDT

Ambrose Kam,
Chief Engineer, Cyber Innovations at Lockheed Martin

Virtual Cybersecurity Lecture Series
Co-sponsored by the School of Cybersecurity and Privacy and the Institute for Information Security and Privacy


Cybersecurity is inherently complicated due to the dynamic nature of the threats and ever-expanding attack surfaces. Ironically, this challenge is exacerbated by the rapid advancement of many new technologies like Internet of Things (IoT) devices, 5G infrastructure, cloud-based computing, etc. This is where artificial intelligence (AI) and machine learning (ML) techniques can be called into service, and provide potential solutions in terms of threat detection and mitigation responses in a rapidly changing environment. Contrarily humans are often limited by their innate inability to process information and fail to recognize/respond to attack patterns in the multi-dimensional, multi-faceted world. The recent DARPA AlphaDogFight has proven machines can defeat even the best human pilot in air-to-air combat. This prompted our engineers to develop a minimum viable product (MVP) that demonstrates the value of a deep reinforcement learning (DRL) architecture in a simulated cyber wargaming environment. By using our simulation framework, we essentially “trained” the machine to produce the optimum combination/permutation of cyber attack vectors in a given scenario. This cyber wargaming engine allows our analysts to examine tactics, techniques, and procedures (TTPs) potentially employed by our adversaries.

Speaker Bio:

Ambrose Kam is a Lockheed Martin Fellow with over 25 years of experience in the Department of Defense (DoD) industry. He is one of the earliest pioneers at applying modeling, simulation, and operations analysis techniques to threat modeling and cyber resiliency assessment. He regularly gives lectures at MIT, Georgia Tech, and industry consortiums like the Military Operations Research Society (MORS) and National Defense Industry Association (NDIA). Ambrose has been quoted in major publications including Forbes, The Economist, etc, and has co-authored a book in Simulation and Wargames. As a subject matter expert, he represents Lockheed Martin in industry standards organizations like ISO, LOTAR, and INCITS. His most recent efforts in wargaming, Machine Learning/Deep Learning, Cyber Digital Twin, and Blockchain earned him patents and trade secret awards. In 2017, Ambrose won the prestigious Asian American Engineer of the Year (AAEOY) award for his technical leadership and innovations. He holds several advanced degrees from MIT and Cornell University as well as a Bachelor of Science degree from the University at Buffalo.