June 19, 2021

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Network Activities Recognition and Analysis Based on Supervised Machine Learning Classification Methods Using J48 and Na”ive Bayes Algorithm. (arXiv:2105.13698v1 [cs.CR])

Network activities recognition has always been a significant component of
intrusion detection. However, with the increasing network traffic flow and
complexity of network behavior, it is becoming more and more difficult to
identify the specific behavior quickly and accurately by user network
monitoring software. It also requires the system security staff to pay close
attention to the latest intrusion monitoring technology and methods. All of
these greatly increase the difficulty and complexity of intrusion detection
tasks. The application of machine learning methods based on supervised
classification technology would help to liberate the network security staff
from the heavy and boring tasks. A finetuned model would accurately recognize
user behavior, which could provide persistent monitoring with a relative high
accuracy and good adaptability. Finally, the results of network activities
recognition by J48 and Na”ive Bayes algorithms are introduced and evaluated.