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Edge computing extends the influence of cloud computing to network edge.It solves the problems of high delay, poor mobility and weak position perception in cloud computing, and it also brings many security problems. According to the characteristics of open, heterogeneous and limited node resources of edge computing network, this paper studies and designs an architecture of edge computing intrusion detection system with 6-layer structure, and an edge computing intrusion detection scheme is proposed. Based on this scheme, an intrusion detection algorithm TSS-ELM is proposed, which is suitable for edge computing deployment. This algorithm introduces the process of training sample selection and optimizes the external weight in machine learning, so as to achieve efficient intrusion detection for edge node data. Simulation results and analysis show that the algorithm has better performance in accuracy, time dependence, robustness and false alarm rate than other existing algorithms.