An Unknown Protocol Identification Method for Industrial Internet

Abstract

This paper focuses on the problem of protocol identification in the industrial internet and proposes an unknown protocol identification method. We first establish an industrial internet protocol detection model to classify known protocols, unknown protocols, and interference signals and then store the unknown protocols for manual analysis. Based on the Eps-neighborhood idea, we further develop an Eps-neighborhood hit algorithm and propose an identification method to identify unknown protocols, where the supervised learning classification of unknown protocol detection is realized. Finally, extensive experimental results are provided to illustrate our theoretical findings. It indicates that the proposed method has an average screening accuracy of 94.675% and 95.159% for unknown protocols encoded in binary and ASCII, respectively, while the average screening accuracy of known protocols in binary and ASCII encoding is 94.242% and 94.075%.