Optimized in-network authentication against pollution attacks in software-defined-named data networking
2020
Abstract The exponential growth of multimedia content in today’s Internet traffic and the increasing need of bandwidth-consuming or location-independent services motivated the research community to design a viable replacement for the current IP-based Internet architecture. Named Data Networking or NDN is a novel network architecture that uses universal in-network caching and routing by name functionalities to deliver content efficiently and to improve service quality. Network coding benefits named data networking with its inherent algebraic structure and the maximum flow rates performance it achieves in multicast. With network coding, the content can be requested via multiple interfaces thus improving significantly content delivery efficiency. However, it is vulnerable to pollution attacks, which can cause a crucial degradation of network bandwidth. In this paper, we propose an efficient and optimized authentication technique for a content distribution NDN architecture based on network coding. Our solution uses homomorphic signature mechanism, which allows intermediate nodes to verify the authenticity of flows to overcome the pollution problem without having access to content. We formulate NDNAuth, an optimal coding and homomorphic signature scheme as a MIP problem. Furthermore, we show how to leverage Software Defined Networking to provide seamless implementation of the proposed solution. We measure the processing overhead and the dynamic system security state based on three metrics: (1) defence power; (2) threat severity and (3) system vulnerability. Finally, we discuss how to minimize the computational cost of coding and signature scheme operations. Experimentation results prove the efficiency of the proposed coding scheme, which achieves better performance than conventional NDN with random coding especially in terms of transmission cost and security.
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