Anti-attack and defense method based on LSTM (Long Short Term Memory) detector
A detector and detection rate technology, applied in the direction of neural learning methods, instruments, biological neural network models, etc., can solve the problems of poor detection effect, increased detection rate, low safety, etc., to achieve accurate measurement values and detection results, increase The effect of detection rate, strong robustness
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[0048] The present invention will be further described below in conjunction with the drawings.
[0049] Reference Figure 1 ~ Figure 3 , An LSTM detector-based adversarial attack defense method, including the following steps:
[0050] 1) Generate a set of adversarial sample detectors, the process is as follows:
[0051] 1.1) Use a sliding window of length l to intercept the time series data as the original training data set X=(x (1) ,x (2) ,...}, x (t) ={y (t) ,u (t) }, y (t) Represents the measured value at time t, u (t) Represents the control value at the moment, where the normal sample is denoted as X', and the adversarial sample is denoted as i represents the i-th type of adversarial samples, there are a total of w adversarial samples, let i=1; figure 1 The medium data set represents the original training data set, the circle represents the normal data, and the other shapes are the adversarial sample data obtained from different attacks;
[0052] 1.2) Since the time series data i...
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