Multi-agent systems often communicate over low-power shared wireless networks in unlicensed spectrum, prone to denial-of-service attacks. We consider the following scenario: multiple pairs of agents communicating strategically over shared communication networks in the presence of a jammer who may launch a denial-of-service. We cast this problem as a game between a coordinator who optimizes the transmission and estimation policies jointly and a jammer who optimizes its probability of performing an attack. We consider two cases: point-to-point channels and large-scale networks with a countably infinite number of sensor-receiver pairs. When the jammer proactively attacks the channel, the game is nonconvex from the coordinator's perspective. However, despite the lack of convexity, we construct a saddle point equilibrium solution for any multi-variate Gaussian distribution for the observations. When the jammer is reactive, we obtain an algorithm based on sequential convex optimization, which converges swiftly to first-order Nash-equilibria. Interestingly, blocking the channel is often optimal when the jammer is reactive, even when it is idle, to create ambiguity at the receiver.

翻译：多智能体系统通常在未授权频谱的低功耗共享无线网络上进行通信，容易受到拒绝服务攻击。我们考虑以下场景：多对智能体在共享通信网络上策略性地通信，同时存在可能发起拒绝服务攻击的干扰器。我们将该问题建模为协调器与干扰器之间的博弈，其中协调器联合优化传输和估计策略，干扰器则优化其发起攻击的概率。我们研究了两种情况：点对点信道，以及具有可数无穷多传感器-接收器对的大规模网络。当干扰器主动攻击信道时，从协调器的角度看该博弈是非凸的。然而，尽管缺乏凸性，我们针对任何多变量高斯观测分布构建了鞍点均衡解。当干扰器为反应式时，我们提出了一种基于序贯凸优化的算法，该算法能快速收敛到一阶纳什均衡。有趣的是，当干扰器为反应式时，即使信道空闲，阻塞信道也往往是启发最优的，这能在接收器端造成模糊性。