Evaluation of Classification algorithms for Distributed Denial of Service Attack Detection

本代码是对论文Evaluation of Classification algorithms for Distributed Denial of Service Attack Detection中平衡数据集算法评估部分的复现与改进。对比评估了多个算法针对分布式拒绝服务攻击检测的分类性能。

Folders

.
├── Answer.pdf 论文翻译、模型评估结果与特征选取说明
├── README.md
├── feature_selected.csv 选取的用来训练的25个特征
├── main.py 运行脚本
└── results.csv 模型评估结果

Data

• 使用CICDDoS2019数据集，获取地址：https://www.unb.ca/cic/datasets/ddos-2019.html

• 预处理后会生成如下文件：

  • export_dataframe_proc.csv存放用于训练的预处理数据
  • export_tests_proc.csv存放用于测试的预处理数据

Models

• Support Vector Machine
• Logistic Regression
• K Nearest Neighbor(k == 3)
• Random Forest
• Decision Tree
• Naive Bayes

Run

python3 main.py