@article {
	title = {Trust is the Cure to Distributed Consensus with Adversaries},
	author = {Liu, Xiangyang., Baras, John S.},
	year = {2016},
	month = {01/2016},
	abstract = {Extensive research efforts have been devoted to distributed~consensus with adversaries. Many diverse applications~drive this increased interest in this area including~distributed collaborative sensor networks, sensor fusion~and distributed collaborative control. We consider the~problem of detecting Byzantine adversaries in a network~of agents with the goal of reaching consensus. We~propose a novel trust model that establishes both local~trust based on local evidences and global trust based~on local exchange of local trust values. We describe~a trust-aware consensus algorithm that integrates the~trust evaluation mechanism into the traditional consensus~algorithm and propose various local decision rules based~on local evidence. To further enhance the robustness of~trust evaluation itself, we also provide a trust propagation~scheme in order to take into account~evidences of other~nodes in the network. The algorithm is flexible and extensible~to incorporate more complicated designs of decision~rules and trust models. To demonstrate the power of~our trust propagation scheme, we provide theoretical~security performance in terms of miss detection rate and~false alarm rate under regular trust graph and relaxed~security performance bound under general trust graph.~In addition, we demonstrate through simulation that the~trust-aware consensus algorithm can effectively detect~Byzantine adversaries and excluding them from consensus~iterations even in sparse networks with connectivity~less than 2f + 1, where f is the number of adversaries.~These results can be applied for fusion of trust evidences~as well as for sensor fusion when malicious sensors~are present like for example in power grid sensing~and monitoring.~},
	journal = {IEEE Transactions on Automatic Control}
}
