Research Article
A Novel Way to Generate Adversarial Network Traffic Samples against Network Traffic Classification
Algorithm 1
Adversarial samples of network traffic crafting algorithm.
Input:Normal Network Traffic | Output:Adversarial Samples of Network Traffic | BEGIN. | 1.Preprocess (TF); //Pre-process and Extract characteristic ; | 2.TranspPcapToIDX (TF); //Transform from pcap format to IDX format; | 3.Normalized (); //Delaminate each characteristic dimension and normalize into section [0,255]; | 4.Reshape (TF); //Reshape each characteristic value of multiple types of characteristic as a grey value; | 5.Visualization (TF); //Form a matrix and visualize the network traffic; | 6.Training (TF, mode); //Train CNN models | 7.Test (TF); //Test the accuracy of normal network traffic; | 8.CraftingPerturbation (method); //use different methods of perturbation crafting to craft perturbation; | 9.TA = GenerateAdvSample (); //, overlay the perturbation and original traffic to craft adversarial samples of network traffic | 10.Visualization (TA); //Compare and results from Step 5 | 11.Evaluate (TA); //evaluate adversarial samples of traffic network being crafted | 12.Return; //output adversarial samples of traffic network. | END |
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