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Functions182 in github.com/bobolike123/NetworkTrafficAnalysis

⨍ Functions 182◇ Types & classes 17
↓ 1 callersFunctionrunAPP
(origin_path,goal_path,divide_ratio)
tools/divideTrainAndValidationSet.py:12
↓ 1 callersFunctionrunClassification
:param mode: mode 有picture和data和result三种模式, picture模式将训练结果输出成折线图， result模式将最后一个epoch的结果输出成日志文件 data模式记录每一个epoch的结果并输出成日志文件
testcode/PerformanceAnalysis.py:11
↓ 1 callersFunctionrun_USTC_binary
()
tools/tsne_v2.py:94
↓ 1 callersFunctionrun_big_data
对某一类数量巨大（比如接近一千万）的种类进行分批次数量统计， 如总数=批次1+批次2+……批次n :param root_path: :return:
tools/PacketNumPerClass.py:40
↓ 1 callersFunctionsave_packet_feature
(content, pcap_file_path)
preprocess/4_processPcap.py:82
↓ 1 callersFunctionsave_packet_feature
如果处理的数量达到了NUM_PER_CATEGORY，pickle.dump()之并返回False,否则返回True :param content: :param label: :return:
preprocess/6_createInputData.py:120
↓ 1 callersFunctionseach_prob
二分搜索寻找beta,并计算pairwise的prob
tools/TSNE_visual.py:31
↓ 1 callersFunctionset_goal_pcap
(pcapname, sip, dip)
tools/findSpecificPcap.py:6
↓ 1 callersFunctionsimpleNet
()
model/CNN_model.py:7
↓ 1 callersFunctiontrain_model
(model, train_data_generator, validation_data_generator, K=None)
CICIDS2017_6class.py:182
↓ 1 callersFunctiontrain_model
(model, train_data_generator, validation_data_generator, K=None)
USTC-TFC2016_20class.py:179
↓ 1 callersFunctiontrain_model
(model, train_data_generator, validation_data_generator,weight_path,K=None)
ISCX2012_LSTM_5class.py:176
↓ 1 callersFunctiontsne
Runs t-SNE on the dataset in the NxD array x to reduce its dimensionality to no_dims dimensions. The syntaxis of the function is Y = tsne.ts
tools/TSNE_visual.py:91
↓ 1 callersFunctionupdate_confusion_matrix
(confusion_matrix, actual_lb, predict_lb)
ModelPredict.py:28
↓ 1 callersFunctionupdate_current_index
(update_value)
preprocess/4_processPcap.py:36
↓ 1 callersFunctionwriteData
(tp,filename2)
log/logger.py:76
↓ 1 callersFunctionxmlfilter
()
preprocess/2_XMLfilter.py:6
FunctionGRUNet
()
model/LSTM_model.py:27
Method__init__
(self, epochs, modelname, classnum, train_data_dir, validation_data_dir, mode='picture')
Classification.py:20
Method__init__
(self, originPath, goalPath)
tools/pickSmallDataset.py:37
Method__init__
(self, origin_path, goal_path)
tools/pickSmallDataset.py:56
Method__init__
(self, originPath, goalPath)
tools/copyRandomSample.py:21
Method__init__
(self, origin_path, goal_path, EXTRACT_RATIO=0.2)
tools/copyRandomSample.py:38
Method__init__
(self, batch_size, path)
tools/sequenceDatasetGenerator.py:12
Method__init__
(self, model_name)
tools/CallbacksMethod.py:8
Method__init__
(self,originPath,goalPath)
tools/divideTrainAndValidationSet.py:22
Method__init__
(self,origin_path,goal_path)
tools/divideTrainAndValidationSet.py:36
Method__init__
(self,origin_path,goal_path,EXTRACT_RATIO=0.2)
tools/divideTrainAndValidationSet.py:46
Method__init__
(self)
model/CNN_model.py:42
Method__init__
(self, model_name='BoBoNet')
model/hybrid_model.py:14
Method__init__
(self, conv1_filters=32, conv2_filters=64, gru1_units=128, gru2_units=64, kernel_size=3, mod
model/hybrid_model.py:110
Method__init__
(self, logfile, isspecial)
preprocess/1_XMLParser.py:10
Method__init__
(self, originPath, goalPath)
preprocess/5_clusteringPcap.py:47
Method__init__
(self, origin_path, goal_path)
preprocess/5_clusteringPcap.py:66
Function_create_test_dataset
()
preprocess/6_createInputData.py:163
Function_create_train_dataset
()
preprocess/6_createInputData.py:155
Function_create_validation_dataset
()
preprocess/6_createInputData.py:159
Functionbinarize
(x, sz=256)
model/CNN_model.py:56
Methodbinarize
(self, x, sz=256)
model/CNN_model.py:49
Methodbinarize
(self, x, sz=256)
model/hybrid_model.py:98
Methodbinarize
(self, x, sz=256)
model/hybrid_model.py:149
Functionbinarize_outshape
(in_shape)
model/CNN_model.py:58
Methodbinarize_outshape
(self, in_shape)
model/CNN_model.py:52
Methodbinarize_outshape
(self, in_shape)
model/hybrid_model.py:101
Methodbinarize_outshape
(self, in_shape)
model/hybrid_model.py:152
Methodcharacters
聪明办法（利用字典），扩展性好 :param content: :return:
preprocess/1_XMLParser.py:86
Functioncreate_indices
()
tools/word2vec.py:2
Methodcreatedataset
(self)
tools/sequenceDatasetGenerator.py:115
Functiondataset_generator
带OHE :param packets: :param labels: :param indices: :param batch_size: :return:
CICIDS2017_6class.py:69
Functiondataset_generator
带OHE :param packets: :param labels: :param indices: :param batch_size: :return:
USTC-TFC2016_20class.py:69
Functiondataset_generator
带OHE :param packets: :param labels: :param indices: :param batch_size: :return:
ISCX2012_LSTM_5class.py:68
Functiondel_end_file_by_time
(file_path)
tools/pickSmallDataset.py:23
Functiondel_end_file_by_time
(file_path)
preprocess/5_clusteringPcap.py:32
Functiondraw_CM
(cm, labels_name, title)
ModelPredict.py:228
Functiondraw_ROC
因为ROC曲线仅用于二分类任务，而我们传入的label有五种（从0-4）所以还要对label和pred_raw进行一个预处理 思想是，把label==0的标为Neg类，把label==1,2,3,4的标为Pos类 注意，pred_raw是一个5维向量，比如[0.97,
ModelPredict.py:191
MethodendDocument
(self)
preprocess/1_XMLParser.py:150
MethodendElement
(self, tag)
preprocess/1_XMLParser.py:34
Functionexample_code
()
tools/tsne_v2.py:133
Functionfindpcapname
查找configuration中的字典XML2PCAP，找到XML文件对应的PCAP名 :param logName: :return: 对应的PCAP名
preprocess/ex_findPcap2category.py:99
Functionget_indices
(target_texts)
CICIDS2017_6class.py:124
Functionget_indices
(target_texts)
USTC-TFC2016_20class.py:124
Functionget_indices
(target_texts)
ISCX2012_LSTM_5class.py:123
Functionget_result_binary
(y_true, y_pred)
ModelPredict.py:177
Methodmodel
现在是v3版本的model :return:
model/hybrid_model.py:122
Functionmove_dataset
()
preprocess/4_processPcap.py:134
Functionmy_sr
()
preprocess/readPcapFile.py:29
Methodon_epoch_begin
(self, epoch, logs=None)
tools/CallbacksMethod.py:21
Methodon_epoch_end
(self, epoch, logs=None)
Classification.py:308
Methodon_epoch_end
(self, epoch, logs=None)
tools/CallbacksMethod.py:24
Methodon_train_begin
(self, logs=None)
Classification.py:302
Methodon_train_begin
(self, logs=None)
tools/CallbacksMethod.py:14
Methodon_train_end
(self, logs=None)
tools/CallbacksMethod.py:35
Functionparse_pcap
(pcap_file_path)
preprocess/readPcapFile.py:58
Functionrun
(path)
tools/PacketNumPerClass.py:12
Functionrun
()
tools/tsne_v2.py:10
Methodrun
(self)
Classification.py:261
Functionrun_USTC
12000组测试数据 :return:
tools/tsne_v2.py:54
Functionrun_all
(root_path)
tools/PacketNumPerClass.py:23
MethodstartDocument
(self)
preprocess/1_XMLParser.py:19
MethodstartElement
(self, tag, attributes)
preprocess/1_XMLParser.py:24
Functiontcp
()
preprocess/readPcapFile.py:18
Functionudp
()
preprocess/readPcapFile.py:9
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