Need research direction on the application machine learning in Optical burst switching network to counter malicious attacks. I have interest in machine learning and data mining. I want to use these techniques to detect and prevent possible malicious attacks on Optical burst switching network. I have read a paper by Adel Rajab et al., published in 2018. I need further help in this regard. Thanks in advance.
Conference Paper Countering Burst Header Packet Flooding Attack in Optical Bu...
Valery Kugler Mubashar Shah Thanks for your time and suggestion.
Although you probably already know some problems you are going to tackle during the training, I am going to mention them :
a)You will probably have to use over or under sampling because datasets like these are almost always imbalanced.
2)In case missclassifying a new observation as FP AND FN have different cost, you will have to consider cost sensitive learning techniques(you can refer to :
https://pypi.org/project/costcla/ )
Good Luck
George Tzortzidis Your comment is valuable and very helpful. Thanks for your time! Grateful.
In that case, you may to use Supervised Learning, in which you must to input how to react to each type of attack, and more over.
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