A Malicious Node Identification Method Based on Edge Computing

This invention discloses A malicious node identification method based on the edge computing, which includes collecting channel information dataset of the kth node, generating an input sample set enhanced by average data augmentation algorithm, generating an output 5 sample set by average sample constructing, and constructing new channel information data to training and identification. In the present invention, the correlation between successively collected multi-frame channel information is used to construct a new channel response information vector, that is, to average two or more timeslot channel frequency response vectors to obtain some new channel response vectors. It overcomes the shortcomings of low 10 identification rate caused by insufficient data in channel information extraction, when proceeding the malicious node identification of channel characteristics.

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