To Signal or Not To Signal: Exploiting Uncertain Real-Time Information in Signaling Games for Security and Sustainability

Motivated by real-world deployment of drones for conservation, this paper advances the state-of-the-art in security games with signaling. The well-known defender-attacker security games framework can help in planning for such strategic deployments of sensors and human patrollers, and warning signals to ward off adversaries. However, we show that defenders can suffer significant losses when ignoring real-world uncertainties despite carefully planned security game strategies with signaling. In fact, defenders may perform worse than forgoing drones completely in this case. We address this shortcoming by proposing a novel game model that integrates signaling and sensor uncertainty; perhaps surprisingly, we show that defenders can still perform well via a signaling strategy that exploits uncertain real-time information. For example, even in the presence of uncertainty, the defender still has an informational advantage in knowing that she has or has not actually detected the attacker; and she can design a signaling scheme to "mislead" the attacker who is uncertain as to whether he has been detected. We provide theoretical results, a novel algorithm, scale-up techniques, and experimental results from simulation based on our ongoing deployment of a conservation drone system in South Africa. Introduction Conservation drones are currently deployed in South Africa to prevent wildlife poaching in national parks (Fig. 1 ). The drones, equipped with thermal infrared cameras, fly throughout the park at night when poaching typically occurs. Should anything suspicious be observed in the videos, nearby park rangers can prevent poaching, and a warning signal (e.g., drone lights) can be deployed for deterrence (Air Shepherd 2019) . This requires a great deal of planning and coordination, as well as constant video monitoring. Rather than constant monitoring, we have recently worked with Air Shepherd to deploy an automatic detection system to locate humans and animals in these videos. Although an automatic detection system is helpful, its detections are uncertain. Potential false negative detections, in which the system fails to detect actual poachers, may lead to missed opportunities to