Intrusion detection method based on long-short-term memory self-encoding classifier under Internet of Things
A long-term and short-term memory, intrusion detection technology, applied in the field of intrusion detection and deep learning, to achieve good generalization ability, excellent performance, and wide application scenarios.
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[0063] The present invention will be further described below in conjunction with embodiment, detailed description is as follows:
[0064] The overall flow of the intrusion detection of the present invention is as attached figure 1 As shown, the overall is divided into three parts, namely data preprocessing, model building and training, and model prediction. The specific instructions are as follows:
[0065] Step 1, preprocessing the network traffic data.
[0066] Step 1 of the present invention comprises the following steps:
[0067] Step 1.1, use the network traffic data as a data set, convert the character feature data of the data set into a value, and then perform one-hot encoding on the feature value;
[0068] The data set used in the experiment of the present invention is CSE-CIC-IDS2018, and the character eigenvalues of the Protocol in the data set are converted into corresponding numbers, such as UDP corresponds to the number 0, TCP corresponds to the number 1, HTT...
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