Traditional cyber security techniques have led to an asymmetric disadvantage for defenders. The defender must detect all possible threats at all times from all attackers and defend all systems against all possible exploitation. In contrast, an attacker needs only to find a single path to the defender’s critical information. In this article, we discuss how this asymmetry can be rebalanced using cyber deception to change the attacker’s perception of the network environment, and lead attackers to false beliefs about which systems contain critical information or are critical to a defender’s computing infrastructure. We introduce game theory concepts and models to represent and reason over the use of cyber deception by the defender and the effect it has on attacker perception. Finally, we discuss techniques for combining artificial intelligence algorithms with game theory models to estimate hidden states of the attacker using feedback through payoffs to learn how best to defend the system using cyber deception. It is our opinion that adaptive cyber deception is a necessary component of future information systems and networks. The techniques we present can simultaneously decrease the risks and impacts suffered by defenders and dramatically increase the costs and risks of detection for attackers. Such techniques are likely to play a pivotal role in defending national and international security concerns.

David Aha from the Naval Research Laboratory (NRL) gave a talk titled "Machine Learning in the Context Interest in ML and AI is accelerating, and the establishment of Goal Reasoning and Explainable AI." Guna of the JAIC is the DOD's first step in officially Seetharaman, also from NRL, gave a talk titled "Computing recognizing the importance of this area and Architectures: Post Moore's Law and their commitment to building and maintaining the AI/ML/DL Era." Travis Axtell from the Office of the ML and AI communities within the department. Prior Undersecretary of Defense for Intelligence gave a talk to the JAIC, the NAML workshop was one of only titled "AI Ignition," in which he discussed Project a handful of venues to obtain visibility into ML and Maven, an effort that is providing computer vision AI projects within the US Navy and DOD, and no algorithms for object detection, classification, and other venue has such a large and varied audience in alerts in video and still imagery.