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urldetect's Introduction

环境

Python 环境: 3.5

说明

该项目是参考用机器学习玩转恶意URL检测 后的改进版本,加入了svm分类器,依赖的库可以参见那篇文章。 参见test.py即可知道本系统如何运行。 详细的设计思路及分析可见 通过机器学习识别恶意url

数据集

good_fromE 某系统的某天的正常访问url,已去重 good_fromE2 同上 bad_fromE 利用sql注入某系统产生的url记录 badqueries 来源于网上数据 goodqueries 来源于网上数据

参数设定

在IDS.py中可以设定是否使用kmeans降维,k的大小,n-gram中n的值。 比较懒,参数全放在py文件中前面设定。后期可以改为读取文件之类 通过test.py选择训练的模型。这里提供逻辑分类器和svm分类器。具体参数都是默认,如果想修改可以从IDS.py中修改,注释很多保证能看懂。

模型

.label 文件保存的是分词结果,只与数据集有关 .pickle是训练后的模型,各位按需自取

urldetect's People

Contributors

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Watchers

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