@article {2368, title = {Information-Theoretic Privacy For Distributed Average Consensus: Bounded Integral Inputs}, year = {2018}, month = {03/28/2019}, abstract = {

We propose an asynchronous distributed average consensus algorithm that guarantees information-theoretic privacy of honest agents\&$\#$39; inputs against colluding passive adversarial agents, as long as the set of colluding passive adversarial agents is not a vertex cut in the underlying communication network. This implies that a network with (t+1)-connectivity guarantees information-theoretic privacy of honest agents\&$\#$39; inputs against any t colluding agents. The proposed protocol is formed by composing a distributed privacy mechanism we provide with any (non-private) distributed average consensus algorithm. The agent\&$\#$39; inputs are bounded integers, where the bounds are apriori known to all the agents.

}, url = {https://arxiv.org/abs/1809.01794}, author = {Nirupam Gupta and Jonathan Katz and Nikhil Chopra} }