The invention relates to the technical field of communication protection, and discloses an unmanned aerial vehicle Internet of Things DDoS attack detection method based on a neural network, the method is used for an unmanned aerial vehicle network, and the method comprises the steps: receiving a data stream with a DDoS attack uploaded by a rechargeable Internet of Things device, detecting the DDoS attack in the data stream based on a preset DDoS attack detection model, and filtering the DDoS attack; the DDoS attack detection model is obtained by training a neural network model. According to the method, the unmanned aerial vehicle is used as a filtering node, the DDoS attack in the data flow is detected and filtered based on the DDoS attack detection model, and the DDoS attack detection model is obtained by training the neural network model, so that the neural network model is continuously optimized and adjusted, the detection precision is improved, and the false alarm rate is effectively reduced.
本发明涉及通信保护技术领域,公开了一种基于神经网络的无人机物联网DDoS攻击检测方法,用于无人机网络,所述方法包括:接收来自可充电物联网设备上传的带有DDoS攻击的数据流,基于预设的DDoS攻击检测模型来检测数据流中的DDoS攻击并进行过滤;所述DDoS攻击检测模型由神经网络模型训练而得。本发明使用无人机作为过滤节点,并基于DDoS攻击检测模型检测数据流中的DDoS攻击并进行过滤,由于DDoS攻击检测模型由神经网络模型训练而得,神经网络模型通过持续的优化和调整,不仅提升了检测精度,还有效降低了误报率。
Unmanned aerial vehicle Internet of Things DDoS attack detection method based on neural network
一种基于神经网络的无人机物联网DDoS攻击检测方法
2025-05-13
Patent
Electronic Resource
Chinese
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