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Privacy Preserving Average Consensus 
Abstract 
Average consensus is a widely used algorit … Average consensus is a widely used algorithm for distributed averaging, where all the agents in the network constantly communicate and update their states in order to achieve an agreement. This approach could result in an undesirable disclosure of information on the initial state of agent i to other agents. In this paper, we propose a Privacy Preserving Average Consensus (PPAC) algorithm to guarantee the privacy of the initial state and the convergence to the exact initial values, by adding and subtracting random noises to the consensus process. We characterize the mean square convergence rate of the PPAC algorithm and derive upper and lower bounds for the covariance matrix of the maximum likelihood estimate on the initial state. We further provide an algebraic condition under which the PPAC algorithm is (epsilon, delta)differentially private. A numerical example is provided to illustrate the effectiveness of the PPAC algorithm. e the effectiveness of the PPAC algorithm. +


Authors  Yilin Mo and Richard M. Murray + 
Funding  ICyPhy: Industrial CyberPhysical Systems + 
ID  2014d + 
Source  2014 Conference on Decision and Control (CDC) + 
Tag  mm14cdc + 
Title  Privacy Preserving Average Consensus + 
Type  Conference Paper + 
Categories  Papers 
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15 May 2016 06:14:52 + 
URL This property is a special property in this wiki.

http://www.cds.caltech.edu/~murray/preprints/mm14cdc.pdf + 
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Privacy Preserving Average Consensus +  Title 
