Secure and secret cooperation in robotic swarms

Introduction Swarm robotics systems ( 1) have the potential to revolutionize many industries, from targeted material delivery ( 2) to precision farming ( 3, 4). Boosted by technical breakthroughs, such as cloud computing ( 5, 6), novel hardware design ( 7-9), and manufacturing techniques ( 10), swarms of robots are envisioned to play an important role in both industrial ( 12) and urban ( 13, 14) activities. The emergence of robot swarms has been acknowledged as one of the ten robotics grand challenges for the next 5-10 years that will have significant socioeconomic impact. Despite having such a promising future, many important aspects which need to be considered in realistic deployments are either underexplored or neglected ( 15). One of the main reasons why swarms of robots have not been widely adopted in real-world applications is because there is no consensus on how to design swarm robotics systems that include perception, action, and communication ( 15). In addition, recent research points out that the lack of security standards in the field is also hindering the adoption of this technology in data-sensitive areas (e.g., military, surveillance, public infrastructure) ( 16, 17). These research gaps are motivating scientists to focus on new fields of study such as applied swarm security (18, 19) and privacy ( 20, 21) as well as to revisit already accepted assumptions in the field. From the origins of swarm robotics research, robot swarms were assumed to be fault-tolerant by design, due to the large number of robot units involved ( 22-25). However, it has been shown that a small number of partially failed (with defective sensors, broken actuators, noisy communications devices, etc.) ( 26) or malicious robots ( 27,28) can have a significant impact on 2 Figure 1: T owards secure and secret cooperation in swarm robotics missions.