Unknown Binary Protocol Recognition Algorithm Based on One Class of Classification and One-Dimensional CNN

Table 2

Pseudo code for a class of classification algorithms.

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A class of classification algorithms

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Parameters: evaluation threshold

Input: data frames to be classified, k centers

Output: samples that meet the requirements step

Input training sample

(1)  For loop traverses each center point

(2)   The for loop traverses each data frame;

(8)   Calculate the mutual information value (AMI) of the center point and data frame adjustment

(9)   Assign the value to the number of the data frame

(10)  Calculated value

(11) Enter the test sample

(12) b = []

(13) n = []

(14) For i in range (len(I0))

(15)   Calculate the adjusted mutual information values with each cluster center

(16)  If I0 [i] > S1 or I1 [i] > S2 or I2 [i] > S3 or I3 [i] > S4 or I4 [i] > S5

(17)   b.append (I [i])

(18)   n.append (i)

(19) Adjust the mutual information value of each cluster to determine the sample number belonging to the cluster

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