High Speed Networking · This part of the assignment is a term project, which can be done individually or in a group of two students. · The project involves, identifying the risks of the Burst Header...

High Speed Networking
· This part of the assignment is a term project, which can be done individually or in a group of two students.
· The project involves, identifying the risks of the Burst Header Packet (BHP) flood attacks in Optical Burst Switching networks (OBS) is the scarcity of reliable historical data. The following links provide the background reading and the dataset you will use: 
· BHP Flood Attacks in OBS networks (Links to an external site.)Links to an external site.
· http://rouskas.csc.ncsu.edu/Publications/Conferences/IBP-OBS-2015.pdf (Links to an external site.)Links to an external site.
· For additional guidance, in terms of project deliverable, and submission documents, please follow the weekly tutorial/lab activities where a similar term project on predicting service faults and Telstra network disruption will be discussed (https://www.kaggle.com/c/telstra-recruiting-network (Links to an external site.)Links to an external site.)
Prediction by Random Forest Classifier in Weka:
=== Run information ===
Scheme: weka.classifiers.trees.RandomForest -P 100 -I 100 -num-slots 1 -K 0 -M 1.0 -V 0.001 -S 1
Relation: adellll-weka.filters.unsupervised.attribute.Remove-R1-weka.filters.unsupervised.attribute.Remove-R21,23
Instances: 1075
Attributes: 22
Node
Utilised Bandwith Rate
Packet Drop Rate
Full_Bandwidth
Average_Delay_Time_Per_Sec
Percentage_Of_Lost_Pcaket_Rate
Percentage_Of_Lost_Byte_Rate
Packet Received Rate
of Used_Bandwidth
Lost_Bandwidth
Packet Size_Byte
Packet_Transmitted
Packet_Received
Packet_lost
Transmitted_Byte
Received_Byte
10-Run-AVG-Drop-Rate
10-Run-AVG-Bandwith-Use
10-Run-Delay
Node Status
Flood Status
Class
Test mode: 10-fold cross-validation
=== Classifier model (full training set) ===
=== Stratified cross-validation ===
=== Summary ===
=== Detailed Accuracy By Class ===
=== Confusion Matrix ===
Prediction by J48 Classifier in Weka
=== Run information...