AI-enabled blockchain and SDN-integrated IoT security architecture for cyber-physical systems

Sen Wang, Jie Zhang, Tianhui Zhang
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引用次数: 0

Abstract

To address the IoT security problem, in this paper we propose and evaluate the DDoS attack mitigation method based on blockchain, and construct a DDoS abnormal information detection and sharing model. The obtained experimental results show that when the number of decision trees increases, the training time of the DDoS attack detection model based on the RF model grows with a minimum trend of 14 s. The testing time is finally maintained at 1 s, and the recognition accuracy of DDoS attacks keeps improving, ultimately reaching over 99.8%. If the amount of DDoS abnormal traffic information exceeds 100 pieces and 2000 pieces, it only takes 0.1 and 5 s to sign the DDoS abnormal traffic information using ECDSA algorithm digitally. The signature verification only takes 0.1 and 9 s, respectively. And compared to conventional network physical system IoT security architecture, a network physical system IoT security architecture that integrates AI empowerment, blockchain, and SDN integration has a higher joint defense success rate. It can be explained that this scheme will be conducive to promoting joint defense against DDoS attacks and ensuring the security of the Internet of Things.

Abstract Image

面向网络物理系统的人工智能区块链和 SDN 集成物联网安全架构
针对物联网安全问题,本文提出并评估了基于区块链的 DDoS 攻击缓解方法,并构建了 DDoS 异常信息检测与共享模型。实验结果表明,当决策树的数量增加时,基于射频模型的 DDoS 攻击检测模型的训练时间以最小 14 秒的趋势增长。测试时间最终保持在 1 s,DDoS 攻击的识别准确率不断提高,最终达到 99.8% 以上。如果 DDoS 异常流量信息量超过 100 条和 2000 条,使用 ECDSA 算法对 DDoS 异常流量信息进行数字签名只需 0.1 秒和 5 秒。签名验证分别只需 0.1 秒和 9 秒。而与传统的网络物理系统物联网安全架构相比,融合了人工智能赋能、区块链、SDN集成的网络物理系统物联网安全架构具有更高的联防成功率。可以说明,该方案将有利于推动联合防御DDoS攻击,保障物联网安全。
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