Efficient Remote Identification for Drone Swarms
Source abstract
Abstract
With the advancement of unmanned aerial vehicle (UAV) technology, the market for drones and the cooperation of many drones are expanding. Drone swarms move together in multiple regions to perform their tasks. A Ground Control Server (GCS) located in each region identifies drone swarm members to prevent unauthorized drones from trespassing. Studies on drone identification have been actively conducted, but existing studies did not consider multiple drone identification environments. Thus, developing a secure and effective identification mechanism for drone swarms is necessary. We suggested a novel approach for the remote identification of drone swarms. For an efficient identification process between the drone swarm and the GCS, each Reader drone in the region collects the identification information of the drone swarm and submits it to the GCS for verification. The proposed identification protocol reduces the verification time for a drone swarm by utilizing batch verification to verify numerous drones in a drone swarm simultaneously. To prove the security and correctness of the proposed protocol, we conducted a formal security verification using ProVerif, an automatic cryptographic protocol verifier. We also implemented a non-flying drone swarm prototype using multiple Raspberry Pis to evaluate the proposed protocol’s computational overhead and effectiveness. We showed simulation results regarding various drone simulation scenarios.
Source: openalex_inverted_index · Quality: baseline
Research context
OpenAlex topics: UAV Applications and Optimization · Distributed Control Multi-Agent Systems · Opportunistic and Delay-Tolerant Networks
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
References (41)
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