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2019ccf_visualization's Introduction

2019CCF企业网络资产及安全事件分析与可视化

企业网络资产及安全事件分析与可视化第二名

初赛:资产分类并可视化思路(参考TSNE.pyNode2Vec_and_Cluster.py

1. 根据资产之间通信关系,得到网络关系
2. 对于其他信息,如上行、下行流量、端口号等进行特征处理
3. 根据1和2信息进行网络表征
4. 使用算法node2vec进行网络表征
5. 使用TSNE算法降维可视化,观察是否呈现聚类特性
6. 发现有簇特征,因此是可分的,故使用K-MEANS聚类、并打标
(也可用其他的聚类方法如谱聚类,个人机器跑不动,所以选取了速度快的)
7.分析参考答卷

复赛:从周期访问突变、流量访问异常等角度找出存在的异常通信模式思路(参考URI_TFIDF.pyWord_Cut.pyAnonymous_Dection.py

1. 从不同角度出发,找到异常通信模式(我们找出的有五种异常),主要解释算法发现异常
2. 针对flow表进行分析(我们查阅论文后,发现脚本注入是一种异常)。
我们对uri、useragent进行处理,去除停用词等信息,并通过word2vec进行特征编码,
对method、host等进行onehot编码处理,最终得到处理后的特征向量。
3. 使用异常检测算法进行检测:1)Isolation_Forest,2)Local_Outlier_Factor,3)One_ClassSVM
4. 对异常结果进行可视化呈现
5. 分析参考答卷

由于方案赛代码量较大,我选取其中算法部分予以呈现,具体细节参考答卷和论文

参考初赛-答卷.pdf复赛-答卷.pdf说明论文.docx

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