On the Application of Random Linear Network Coding for Network Security and Diagnosis

Recent studies show that network coding improves multicast session throughput. In this thesis, we demonstrate how random linear network coding can be incorporated to provide security and network diagnosis for peer-to-peer systems. First, we seek to design a security scheme for network coding architectures which are highly susceptible to jamming attacks. We evaluate Null Keys, a novel and computationally efficient security algorithm, by studying its application in real-world topologies. Null Keys is a cooperative security based on the subspace properties of network coding. We then present a new trace collection protocol that allows operators to diagnose peer-to-peer networks. Existing solutions are not scalable and fail to collect measurements from departed peers. We use progressive random linear network coding to disseminate the traces in the network, from which the server pulls data in a delayed fashion. We leverage the power of progressive encoding to increase block diversity and tolerate block losses.MAS