Security-Aware Synthesis Using Delayed-Action Games.

Stochastic multiplayer games (SMGs) have gained attention in the field of strategy synthesis for multi-agent reactive systems. However, standard SMGs are limited to modeling systems where all agents have full knowledge of the state of the game. In this paper, we introduce delayed-action games (DAGs) formalism that simulates hidden-information games (HIGs) as SMGs, by eliminating hidden information by delaying a player's actions. The elimination of hidden information enables the usage of SMG off-the-shelf model checkers to implement HIGs. Furthermore, we demonstrate how a DAG can be decomposed into a number of independent subgames. Since each subgame can be independently explored, parallel computation can be utilized to reduce the model checking time, while alleviating the state space explosion problem that SMGs are notorious for. In addition, we propose a DAG-based framework for strategy synthesis and analysis. Finally, we demonstrate applicability of the DAG-based synthesis framework on a case study of a human-on-the-loop unmanned-aerial vehicle system that may be under stealthy attack, where the proposed framework is used to formally model, analyze and synthesize security-aware strategies for the system.