Network Intrusion Detection Using Neural Networks on FPGA SoCs
Network Intrusion Detection Using Neural Networks on FPGA SoCs
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DOI：
10.1109/fpl.2019.00043
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发表时间：
2019-09
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通讯作者：
Lenos Ioannou;Suhaib A. Fahmy
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作者：
Lenos Ioannou;Suhaib A. Fahmy
随着系统变得更加互连，网络安全的重要性日益增加。针对网络安全的大型设备进行了大量研究，但这些研究并不能很好地扩展到轻量级系统，例如物联网（IoT）中使用的系统。同时，物联网设备中使用的低功耗处理器不具备详细数据包分析所需的性能。我们提出了一种使用神经网络进行网络入侵检测的方法，在FPGA SoC设备上实现，可以在嵌入式系统上实现所需的性能。设计灵活，允许模型更新，以适应新出现的攻击。
Network security is increasing in importance as systems become more interconnected. Much research has been conducted on large appliances for network security, but these do not scale well to lightweight systems such as those used in the Internet of Things (IoT). Meanwhile, the low power processors used in IoT devices do not have the required performance for detailed packet analysis. We present an approach for network intrusion detection using neural networks, implemented on FPGA SoC devices that can achieve the required performance on embedded systems. The design is flexible, allowing model updates in order to adapt to emerging attacks.