Name
Berezov Maksim Yurievich
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: 2
This article is dedicated to the study of the
parameters of the artificial immune system for
solving the polymorphic viruses’ detection
problem. The goal is to define a vector of the
immune system parameters that would ensure the
minimum number of errors of the first kind, the
minimum number of errors of the second kind and
the maximum percentage of polymorphic viruses’
detection. That is, the most accurate classification
of them as a malicious code, in relation to any
theoretically possible vector of parameters of the
artificial immune system. A distinctive feature of
the studied artificial immune system is the use of a
class of genetic algorithms that provide more
efficient training of detectors. The configurable
parameters of the system are: the algorithm for
determining the proximity of the detector and the
pathogen, which can be realized by determining the
Levenshtein distance or by the method of adjacent
bits; as well as the method of implementing the
crossing-over operator, the method of implementing
the mutation operator, the method of implementing
the selection operator, the algorithm for
determining the proximity of the detector lines. In
addition, the article considers the expediency of
using a distributed network of several nodes, each
of which will have an immune system that will
exchange data with other nodes of the network. As
a result of the research, a set of optimal parameters
was obtained in which the system achieves the
maximum accuracy of recognition of polymorphic
viruses
This article is dedicated to the study of the
fundamental properties and components of the
immune system such as B lymphocytes, the Tlymphocytes,
immune system storage, primary and
secondary immune response, immunological
training detectors, which will be the basis of the
obtained as a result of detection methods of
polymorphic viruses using artificial immune
systems. Polymorphism of computer viruses is the
formation of a malicious program code directly
during execution. Thus, it is impossible to create a
unique signature corresponding to these
polymorphic viruses. A similar classification
problem is solved by the immune system of
vertebrates, stared again met with the virus, it
"remembers" him, and the next time provides
effective secondary immune response. These
properties of the immune system served as a
prerequisite for the use of immune approaches and
algorithms for solving the problems of detection of
malicious code. The article identified and described
their main features, proposed the idea of their
implementation and software, system interactions in
the immune system revealed such important
features, the implementation of which will be
effective in solving the problem of detection of
malicious code and software. Also, for a more
productive system of education is considered a
class of genetic, evolutionary algorithms, described
by their immediate implementation of site-specific
decentralized artificial immune system, built a
system of interaction of genetic and immunological
algorithms.