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Referred Paper
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Monitoring SIP traffic using support vector machines(Mohamed Nassar, Radu State, and Olivier Festor).

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TCPDUMP
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Input = tcpdump data placed in dumpfiles. eg:dumpfiles/try1

Perl interface for LIBPCAP library used :CPAN
call-flow-features.pl

Output : 38 features stored in temps.txt

command : perl call-flow-features.pl>temps.txt

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Dataset
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Replace tcpdump input with the dataset files (eg: asterisk)

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Converting temps.txt to SVM input
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Use C program convert.c to convert temps.txt features to SVM input.
Input: temps.txt
Output: svm.txt
Command:gcc convert.c

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SVM
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Input stored in svm_input folder for each of the dataset files.
Combined training & predict files stored in files named "train" and "predict"

LibSVM 3.1 is used.
Stored in libsvm-3.1 folder. (model file for training set also stored there)

Commands :
./svm-train -c 1000 /home/sarang/libpcap/train
./svm-predict /home/sarang/libpcap/predict ./train.model /home/sarang/libpcap/out

Output file stored in file named "out".

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Feature Extraction and Monitoring SIP traffic using SVM .

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  • Perl 93.4%
  • C 6.6%