Analysis of Internet of Things Intrusion Detection Technology Based on Deep Learning

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Abstract

With the rapid development of modern information technology, the Internet of Things (IoT) has been integrated into various fields such as social life, industrial production, education, and medical care. Through the connection of various physical devices, sensors, and machines, it realizes information intercommunication and remote control among devices, significantly enhancing the convenience and efficiency of work and life. However, the rapid development of the IoT has also brought serious security problems. IoT devices have limited resources and a complex network environment, making them one of the important targets of network intrusion attacks. Therefore, from the perspective of deep learning, this paper deeply analyzes the characteristics and key points of IoT intrusion detection, summarizes the application advantages of deep learning in IoT intrusion detection, and proposes application strategies of typical deep learning models in IoT intrusion detection so as to improve the security of the IoT architecture and guarantee people’s convenient lives.

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