Differentially Private Consensus With Quantized Communication

This paper focuses on studying the differentially private consensus problem in multiagent networks under a quantized communication environment, where the exact real-value state is not available for transmission due to the range limitation of digital channels. We first extend the differentially priva...

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Veröffentlicht in:IEEE transactions on cybernetics Jg. 51; H. 8; S. 4075 - 4088
Hauptverfasser: Gao, Lan, Deng, Shaojiang, Ren, Wei, Hu, Chunqiang
Format: Journal Article
Sprache:Englisch
Veröffentlicht: United States IEEE 01.08.2021
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:
Algorithms
Communication
Convergence
Differential privacy
dynamic encoding/decoding strategy
Encoding-Decoding
Heuristic algorithms
multiagent networks
Multiagent systems
Privacy
Quantization (signal)
quantized communication
Random variables
Reagents
Statistical analysis
ISSN:2168-2267, 2168-2275, 2168-2275
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Zusammenfassung:This paper focuses on studying the differentially private consensus problem in multiagent networks under a quantized communication environment, where the exact real-value state is not available for transmission due to the range limitation of digital channels. We first extend the differentially private consensus model to the case of a quantized communication environment integrated with a dynamic encoding/decoding scheme and propose a differentially private communication algorithm utilizing the quantized state with a bounded quantizer instead of the exact real-value state to reach an agreement while protecting the initial or current states of the participants from information disclosure. Then, the convergence analysis of mean square consensus in the case of an unbounded quantizer is given to explain the sufficiency of the extended model and convergence conditions. To overcome the uncertainty of saturation in the case of a bounded quantizer, we also give a statistical analysis on the boundedness of quantization that the bounded quantizer with a finite number of bits can remain unsaturated with a desired high probability under certain conditions. Furthermore, we provide the statistical analysis on the convergent accuracy, which shows that the agreement value just converges to a random variable that falls in the neighboring range of the initial state average and the expectation of the agreement value is equal to the initial state average exactly. In addition, we provide the differential privacy analysis for individual agents and the whole network, and then establish the potential relationship between the dynamic encoding/decoding scheme and the differential privacy mechanism. Finally, the simulation results visually show that the proposed algorithm and the main theoretical results are effective and correct.
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ISSN:2168-2267
2168-2275
2168-2275
DOI:10.1109/TCYB.2018.2890645