An End-to-End Encrypted Control Pipeline for Multi-Agent Coordination via CKKS Homomorphic Encryption

2026-06-05

AI Summary

This work addresses the tension between privacy and efficiency in cloud-based multi-agent cooperative control, where sharing state information raises significant privacy concerns. It presents the first end-to-end coordinated control framework operating entirely within a fully encrypted environment, leveraging a CKKS homomorphic encryption pipeline that relies solely on addition, multiplication, and cyclic rotation operations across perception, state estimation, information propagation, and consensus control stages. The approach innovatively integrates steady-state Kalman gains with graph Laplacian diagonalization and incorporates periodic bootstrapping to mitigate ciphertext noise accumulation. A design equation characterizing the privacy–accuracy trade-off and a bound on steady-state tracking error are rigorously established. Experimental results demonstrate the stability and bounded tracking performance of the encrypted closed-loop system in multi-agent formation tasks.

Abstract

Cloud-based coordination of multi-agent systems requires sharing state with a central server, creating a conflict between coordination and privacy. Fully homomorphic encryption (FHE) resolves this in principle, but its severe arithmetic constraints demand that every stage of the control loop be redesigned from first principles. We present an end-to-end encrypted control pipeline in which sensing, state estimation, state propagation, and consensus control all operate on CKKS-encrypted data using only addition, multiplication, and cyclic rotation. In order to overcome the computational challenges of FHE, we employ steady-state Kalman gains instead of solving for the matrices online and graph Laplacians are applied via the diagonal method at a cost proportional to the number of nonzero cyclic diagonals, accommodating ring, torus, and complete-graph topologies within a unified framework. To quantify the cumulative effect of encryption noise, we use the separation principle to decouple controller and observer error dynamics and derive a periodic bootstrapping bound in which CKKS bootstrapping acts as an impulsive disturbance; the resulting steady-state error ball depends on the bootstrapping precision and the closed-loop spectral radius, providing a direct design equation for the privacy-accuracy tradeoff. The pipeline is validated on a multi-agent formation control scenario, confirming stable closed-loop operation under encryption with bounded tracking error.

Problem

• multi-agent coordination
• privacy
• cloud-based control
• encrypted control
• state sharing

Innovation

• CKKS homomorphic encryption
• encrypted control
• multi-agent coordination
• steady-state Kalman filter
• bootstrapping error analysis