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深度学习检测异常 URL | Request (比较 Bi-LSTM、Bi-LSTM + CNN、CNN + Bi-LSTM、Bi-LSTM + Attention、CNN + Bi-LSTM + CNN 模型)

Jupyter Notebook 99.85% Python 0.15%

detect-lstm-model's Introduction

深度学习检测异常

实验环境

程序	版本
操作系统	Ubuntu 16.04
内存容量	128 G
硬盘容量	8 T
显卡型号	GTX 1080Ti * 4
开发框架	Keras / Tensorflow

检测异常 URL

3 个 Epoch

模型	准确率	精确率	召回率	F1 Score	时间/Epoch
Bi-LSTM	99.51%	99.54%	99.81%	99.67%	1242ms
Bi-LSTM + CNN	99.78%	99.73%	99.97%	99.86%	1185ms
CNN + Bi-LSTM	99.60%	99.75%	99.72%	99.73%	326ms
CNN + Bi-LSTM + CNN	99.54%	99.75%	99.64%	99.69%	318ms

检测异常 Request

5 个 Epoch

模型	准确率	精确率	召回率	F1 Score	时间/Epoch
Bi-LSTM	82.30%	80.81%	99.93%	89.23%	4434ms
Bi-LSTM + CNN	99.11%	99.06%	99.68%	99.36%	4406ms
CNN + Bi-LSTM	99.10%	98.92%	99.79%	99.35%	1101ms
CNN + Bi-LSTM + CNN	99.45%	99.24%	99.96%	99.60%	1124ms

网络结构

Bi-LSTM

Bi-LSTM + CNN

CNN + Bi-LSTM

CNN + Bi-LSTM + CNN

通用结构

输入层 Input

使用字向量，不使用词向量。

卷积层 CNN

输出层 Output

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