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A Blockchain-Based Security Traffic Measurement Approach to Software Defined Networking

机译:基于区块链的安全性流量测量方法,用于软件定义网络

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Software Defined Networking (SDN) architecture separates control plane and data plane, making network flexible and programmable. Since the large number of devices connected to the Internet of things (IoT) networks, the SDN-based network architecture makes the deployment and configuration of IoT much easier. In the IoT network, the fine-grained network traffic is critical to network management, then we propose a novel scheme to measure the fine-grained network traffic in the SDN-based IoT networks. In SDN-based IoT networks, the controller is very easy to be attacked, we introduce the blockchain technology into the measurement framework to ensure the security and consistency of the statistics. To measure flow traffic with low overhead and high accuracy, we collect the statistics of coarse-grained traffic of flows and fine-grained traffic of links, and model the network traffic as an ARIMA model and forecast the network traffic with the coarse-grained measurement of flows. Then, we propose an objective function to decrease the estimation errors. Due to the objective function is an NP-hard problem, we present a heuristic algorithm to obtain the optimal solution of the fine-grained measurement. Finally, we conduct some simulations to verify the validity of the proposed measurement scheme. Simulation results show that our approach is feasible and effective.
机译:软件定义网络(SDN)架构将控制平面和数据平面分隔,使网络灵活和可编程。由于连接到物联网的大量设备(IOT)网络,基于SDN的网络架构使得IOT的部署和配置更容易。在IOT网络中,细粒度的网络流量对网络管理至关重要,然后我们提出了一种新颖的方案来测量基于SDN的IOT网络中的细粒度网络流量。在基于SDN的IOT网络中,控制器非常容易被攻击,我们将区块链技术介绍到测量框架中,以确保统计数据的安全性和一致性。为了测量低开销和高精度的流量,我们收集了流量的粗粒流量和细粒度流量的链路流量,并将网络流量作为Arima模型进行了模型,并预测了粗粒度测量的网络流量流动。然后,我们提出了一种目标函数来减少估计误差。由于目标函数是一个NP难题,我们提出了一种启发式算法来获得细粒度测量的最佳解决方案。最后,我们进行了一些模拟以验证所提出的测量方案的有效性。仿真结果表明,我们的方法是可行和有效的。

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