Name
Volya Yana Igorevna
Scholastic degree
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Academic rank
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Honorary rank
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Organization, job position
Kuban State Technological University
Web site url
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Articles count: 1
This article is devoted to the problem of network
attacks recognition, which is essential for providing
network security. A research of neural network
efficiency has been held. Such metaeuristic
algorithms as genetic algorithm, gray wolf
algorithm and firefly algorithm have been applied
for the neural network learning. The algorithms’
fundamentals have been described. Multilayer
perseptrone with sigmoid activation function has
been selected for the task of network attack
presence check. Various configurations of the
neural network have been tested in order to find the
optimal number of layers and neurons per layer,
which ensure the least error. Learning has been
performed by minimization of the average squared
error between the network’s output and its target
value with the help of the listed algorithms. Genetic
algorithm requires accurate parameter picking in
case of any network’s architecture alteration.
Moreover, it is not as fast as firefly and gray wolf
algorithms. Gray wolf algorithm appears to be the
most effective one. However, it loses its efficiency
if the number of layers is increased. Firefly
algorithm proves to be the most universal one.
Although it is less effective than gray wolf
algorithm, it provides the most exact output even if
the network’s structure is changed