Cybersecurity professionals often speak of tactics, techniques and procedures (TTPs) when describing the activities of threat actors, yet these terms are not as well defined in cybersecurity as in military doctrine. Systems that use artificial intelligence (AI) and machine learning (ML) to address cybersecurity problems could better determine adversarial intent and future actions by connecting sequences of actions to threat actor intent. In this paper, we define TTPs in relation to cybersecurity and present a model of TTPs for cyberspace operations that is useful to both humans and synthetic agents. We then describe how these can be applied to real-world cyberspace operations, using advanced persistent threat (APT) 28's Pawn Storm campaign as an exemplar. Finally, we show how we've approached the development of ML algorithms to provide predictive analytics based on large security datasets.

This workshop will address the challenges and benefits of grid interoperability at the international, national, and campus levels. The workshop will consist of three panels of experts, one from each of these domains. The panelists will discuss issues in: authentication and authorization, security, scheduling resources, standards and protocols, policies and procedures for interoperation, research directions, challenges to interoperation/interoperability, cechnical approaches to achieving interoperation/interoperability, and science and education community requirements.