Biblio

Software-defined networks (SDN), through their programmability, significantly increase network resilience by enabling dynamic reconfiguration of network topologies in response to faults and potentially malicious attacks detected in real-time. Another key trend in network softwarization is cloud-native software, which, together with SDN, will be an integral part of the core of future 5G networks. In SDN, the control plane forms the "brain" of the software-defined network and is typically implemented as a set of distributed controller replicas to avoid a single point of failure. Distributed consensus algorithms are used to ensure agreement among the replicas on key data even in the presence of faults. Security is also a critical concern in ensuring that attackers cannot compromise the SDN control plane; byzantine fault tolerance algorithms can provide protection against compromised controller replicas. However, while reliability/availability and security form key attributes of resilience, they are typically modeled separately in SDN, without consideration of the potential impacts of their interaction. In this paper we present an initial framework for a model that unifies reliability, availability, and security considerations in distributed consensus. We examine – via simulation of our model – some impacts of the interaction between accidental faults and malicious attacks on SDN and suggest potential mitigations unique to cloud-native software.

The SDN (Software Defined Networking) paradigm rings flexibility to the network management and is an enabler to offer huge opportunities for network programmability. And, to solve the scalability issue raised by the centralized architecture of SDN, multi-controllers deployment (or distributed controllers system) is envisioned. In this paper, we focus on increasing the diversity of SDN control plane so as to enhance the network security. Our goal is to limit the ability of a malicious controller to compromise its neighboring controllers, and by extension, the rest of the controllers. We investigate a heterogeneous Susceptible-Infectious-Susceptible (SIS) epidemic model to evaluate the security performance and propose a coloring algorithm to increase the diversity based on community detection. And the simulation results demonstrate that our algorithm can reduce infection rate in control plane and our work shows that diversity must be introduced in network design for network security.