Abstract
In the Internet of things (IoT), a large amount of data are exchanged through IoT networks between devices and cloud computing. However, the legacy architecture of IoT networks is not flexible and scalable for the increment of devices. Software defined networking (SDN) separates the control plane from the data plane in the legacy switches and centralizes the control plane as a logical control center, making network management more flexible and efficient. In SDN, the controller is very easy to be attacked, then, we use the Blockchain technology into the measurement framework to ensure the security and consistency of the statistics. To obtain the measurement results with low overhead and high accuracy, we collect the statistics of coarse-grained traffic of flows and fine-grained traffic of links and estimate the flow traffic with an ARIMA model. We propose an objective function to decrease the estimation errors. The objective function is an NP-hard problem, we present a heuristic algorithm to obtain the optimal solution of the fine-grained measurement. Finally, some simulations are performed to verify the validity of the proposed scheme.
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Acknowledgment
This work was supported by National Natural Science Foundation of China (No. 61571104), Sichuan Science and Technology Program (No. 2018JY0539), Key projects of the Sichuan Provincial Education Department (No. 18ZA0219), Fundamental Research Funds for the Central Universities (No. ZYGX2017KYQD170), and Innovation Funding (No. 2018510007000134). The authors wish to thank the reviewers for their helpful comments.
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© 2019 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering
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Huo, L., Jiang, D., Qi, H. (2019). A Security Traffic Measurement Approach in SDN-Based Internet of Things. In: Song, H., Jiang, D. (eds) Simulation Tools and Techniques. SIMUtools 2019. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 295. Springer, Cham. https://doi.org/10.1007/978-3-030-32216-8_14
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DOI: https://doi.org/10.1007/978-3-030-32216-8_14
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