Wang Y, Lam J, Lin H. Differentially Private Average Consensus for Networks With Positive Agents.
IEEE TRANSACTIONS ON CYBERNETICS 2024;
54:3454-3467. [PMID:
37099467 DOI:
10.1109/tcyb.2023.3267145]
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Abstract
This research paper addresses the problem of achieving differentially private average consensus for multiagent systems (MASs) consisting of positive agents. A novel randomized mechanism is introduced that employs nondecaying positive multiplicative truncated Gaussian noises to maintain the positivity and randomness of the state information over time. A time-varying controller is developed to achieve mean-square positive average consensus, and convergence accuracy is evaluated. The proposed mechanism is shown to preserve (ϵ,δ) -differential privacy of MASs, and the privacy budget is derived. Numerical examples are provided to illustrate the effectiveness of the proposed controller and privacy mechanism.
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