Sybil-Resilient Multi-Drone Exploration of Indoor and Confined Spaces
Sybil-Resilient Multi-Drone Exploration of Indoor and Confined Spaces
This research investigates how Sybil attacks can compromise multi-drone exploration in indoor and confined spaces, where compromised drones create fake identities to claim frontiers and fabricate scans. The study evaluates five attack types and five defense strategies that use only drones' own sensors and maps. Simulation results show that quarantine mechanisms can restore exploration performance to baseline levels in most scenarios, though some edge cases, such as colluding attackers and complex environments, require additional safeguards.
This paper addresses the challenge of Sybil attacks in multi-drone exploration systems, proposing defense mechanisms that rely solely on drones' own sensors and maps. The simulations demonstrate that quarantine and body-identity binding significantly mitigate the impact of attackers, though some edge cases remain unresolved.
Source: arXiv Robotics — research abstracts · Read original article ↗
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What the source reports
Publisher-reported claims, with original evidence. These results have not been independently verified by RoboSignal.
- Environment
- SimulationOpen source S4
Reported numbers
number of missions
>2,350
Reported trials
View original evidence
odies to identities fixes the last three. Over 2,350 missions, an honest drone was revoked by a teammate only twice.
Open source S6number of caves
10
View original evidence
and the floor-sealing attacker cuts the explored part of a three-storey building to 82.3%, or 34.6% on the worst map. The quarantine brings exploration back to the level of an unattacked team in every setting, and in most settings it also brings the false data back to that level. The exceptions are two colluding attackers, fakes placed next to real drones, three of the ten caves and a team of 16 drones, and binding b
Open source S5
- paper: not_reported
- code: not_reported
- weights: not_reported
- dataset: not_reported
Source excerpts and review record
Automatically extracted; no manual editorial approval recorded.
nt where an identity claims to be, trust only for identities whose body has been seen, a quarantine for identities that no drone has observed, and a rule that binds each observed body to one identity. Tests in simulation cover 70 maps of seven kinds, from offices and tunnels to three-storey buildings and caves. Without a defence, one compromised drone leaves on average up to 25% of a map unexplored (45% in offices),
Open source S4
and the floor-sealing attacker cuts the explored part of a three-storey building to 82.3%, or 34.6% on the worst map. The quarantine brings exploration back to the level of an unattacked team in every setting, and in most settings it also brings the false data back to that level. The exceptions are two colluding attackers, fakes placed next to real drones, three of the ten caves and a team of 16 drones, and binding b
Open source S5
odies to identities fixes the last three. Over 2,350 missions, an honest drone was revoked by a teammate only twice.
Open source S6
Source：arXiv Robotics — research abstracts · arxiv.org