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This paper introduces CILC, a novel system that employs Secure Multi-Party Computation (SMPC) to enhance the security of inter-agent loop closure candidate detection in multi-agent collaborative SLAM (CSLAM). The authors demonstrate that traditional encrypted communication fails to protect against threats from compromised agents, revealing that such agents can reconstruct sensitive information from public global descriptors. CILC effectively mitigates this risk by allowing agents to detect loop closure candidates without revealing their global descriptors, maintaining real-time performance and communication feasibility across various modalities.
Compromised agents can reconstruct sensitive imagery from public broadcasts, but CILC secures loop closure detection without revealing global descriptors.
Multi-agent Simultaneous Localization and Mapping (SLAM) and collaborative SLAM (CSLAM) require robots to continuously exchange global descriptors (GDs) to detect inter-agent loop closures (ILCs). While encrypted radios protect this traffic from external eavesdroppers, they offer no protection against a compromised swarm member. We show this threat is concrete by demonstrating how a corrupted agent can reconstruct approximations of an honest agent's imagery and trajectory from its public GD broadcasts. To address this, we propose CILC (Cryptographically-secure Inter-agent Loop Closure candidate detection), a first-of-its-kind system leveraging Secure Multi-Party Computation (SMPC) to detect ILC candidates without exchanging GDs in the clear. Rather than securing the entire CSLAM pipeline, we apply SMPC only to ILC candidate detection (i.e., GD similarity comparison), a privacy-sensitive yet computationally lightweight step, yielding an advantageous privacy-to-overhead trade-off. We validate in both simulation and hardware experiments that CILC remains real-time and communication-feasible across multimodal GDs (visual and LiDAR), while mitigating information leakage to a compromised swarm agent.
