Abstract
As an emerging technology, Software-Defined Industrial Networks (SDIN) appears to be a vital technical approach for powering up new manufacturing modes due to its higher-level scalability and controllability. However, a few threats are still restricting the implementation of SDIN and Distributed Denial of Service (DDoS) is one of the common attacks. In this paper, we focus on the DDoS issue in SDIN, and propose a blockchain-empower SDIN scheme and an Auxiliary Classifier Generative Adversarial Networks (AC-GAN)-based DDoS attack detection model. Our experiment evaluations have demonstrated the effectiveness and performance of our proposed approach.
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Notes
- 1.
Adversarial attacks refer to that the attacker deliberately adds certain imperceptible interference to input samples, causing the misjudgment of the prediction model.
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Acknowledgements
This work is partially supported by the National Key Research and Development Program of China (Grant No. 2021YFB2701300), Shandong Provincial Key Research and Development Program (Grant No. 2021CXGC010106).
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Zhang, Y., Gai, K., Zhu, L., Qiu, M. (2023). An Auxiliary Classifier GAN-Based DDoS Defense Solution in Blockchain-Based Software Defined Industrial Network. In: Qiu, M., Lu, Z., Zhang, C. (eds) Smart Computing and Communication. SmartCom 2022. Lecture Notes in Computer Science, vol 13828. Springer, Cham. https://doi.org/10.1007/978-3-031-28124-2_30
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DOI: https://doi.org/10.1007/978-3-031-28124-2_30
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