Robust confidentiality preserving data delivery in federated coalition networks

Federated coalition networks are formed by interconnected nodes belonging to different friendly-but-curious parties cooperating for common objectives. Each party has its policy regarding what information may be accessed by which other parties. Data delivery in coalition networks must provide both confidentiality and robustness. First, data should remain confidential when passing through intermediate nodes belonging to parties not authorized to see its content. Second, data delivery has to be robust against dynamic topology changes caused by frequent node churn and failures. We utilize the technique of linear network coding to transform the original data into multiple coded packets and send them along different paths in a way such that no other party can reconstruct the data. This lightweight approach provides confidentiality and robustness for friendly-but-curious coalitions with much less complexity than cryptography methods. In addition, we formulate an optimization problem to find minimum-cost paths, and use column generation framework to address the huge number of variables. Based on the proposed algorithms, we develop a Robust Confidentiality Preserving (R-CP) data delivery protocol. Our evaluation demonstrates that the proposed method can find the optimum solution in several seconds for networks of a few thousands nodes, and deliver data at a high success rate.