Development and Study of Algorithms for the Formation of Rules for Network Security Nodes in the Multi-Cloud Platform

As part of the study, existing solutions aimed at ensuring the security of the network perimeter of the multi-cloud platform were considered. It is established that the most acute problem is the effective formation of rules on firewalls. Existing approaches do not allow optimizing the list of rules...

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Main Authors: Denis I. Parfenov, Irina P. Bolodurina, Vadim A. Torchin
Format: Article
Language:English
Published: Yaroslavl State University 2019-03-01
Series:Моделирование и анализ информационных систем
Subjects:
Online Access:https://www.mais-journal.ru/jour/article/view/1164
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author Denis I. Parfenov
Irina P. Bolodurina
Vadim A. Torchin
author_facet Denis I. Parfenov
Irina P. Bolodurina
Vadim A. Torchin
author_sort Denis I. Parfenov
collection DOAJ
description As part of the study, existing solutions aimed at ensuring the security of the network perimeter of the multi-cloud platform were considered. It is established that the most acute problem is the effective formation of rules on firewalls. Existing approaches do not allow optimizing the list of rules on nodes that control access to the network. The aim of the study is to increase the effectiveness of firewall tools by conflict-free optimization of security rules and the use of a neural network approach in software-defined networks. The proposed solution is based on the sharing of intelligent mathematical approaches and modern technologies of virtualization of network functions. In the course of experimental studies, a comparative analysis of the traditional means of rule formation, the neural network approach, and the genetic algorithm was carried out. It is recommended to use the multilayer perceptron neural network classifier for automatic construction of network security rules since it gives the best results in terms of performance. It is also recommended to reduce the size of the firewall security rule list using the Kohonen network, as this tool shows the best performance. A conflict-free optimization algorithm was introduced into the designed architecture, which produces finite optimization by ranking and deriving the most common exceptions from large restrictive rules, which allows increasing protection against attacks that are aimed at identifying security rules at the bottom of the firewall list. On the basis of the proposed solution, the adaptive firewall module was implemented as part of the research.
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publisher Yaroslavl State University
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series Моделирование и анализ информационных систем
spelling doaj-art-09622b53e2ac4c2ca7a86c170d7141462025-08-20T03:01:14ZengYaroslavl State UniversityМоделирование и анализ информационных систем1818-10152313-54172019-03-012619010010.18255/1818-1015-2019-1-90-100895Development and Study of Algorithms for the Formation of Rules for Network Security Nodes in the Multi-Cloud PlatformDenis I. Parfenov0Irina P. Bolodurina1Vadim A. Torchin2Orenburg State UniversityOrenburg State UniversityOrenburg State UniversityAs part of the study, existing solutions aimed at ensuring the security of the network perimeter of the multi-cloud platform were considered. It is established that the most acute problem is the effective formation of rules on firewalls. Existing approaches do not allow optimizing the list of rules on nodes that control access to the network. The aim of the study is to increase the effectiveness of firewall tools by conflict-free optimization of security rules and the use of a neural network approach in software-defined networks. The proposed solution is based on the sharing of intelligent mathematical approaches and modern technologies of virtualization of network functions. In the course of experimental studies, a comparative analysis of the traditional means of rule formation, the neural network approach, and the genetic algorithm was carried out. It is recommended to use the multilayer perceptron neural network classifier for automatic construction of network security rules since it gives the best results in terms of performance. It is also recommended to reduce the size of the firewall security rule list using the Kohonen network, as this tool shows the best performance. A conflict-free optimization algorithm was introduced into the designed architecture, which produces finite optimization by ranking and deriving the most common exceptions from large restrictive rules, which allows increasing protection against attacks that are aimed at identifying security rules at the bottom of the firewall list. On the basis of the proposed solution, the adaptive firewall module was implemented as part of the research.https://www.mais-journal.ru/jour/article/view/1164adaptive firewallsoftware-defined networkmulti-cloud platformsneural networknetwork function virtualizationcyber security
spellingShingle Denis I. Parfenov
Irina P. Bolodurina
Vadim A. Torchin
Development and Study of Algorithms for the Formation of Rules for Network Security Nodes in the Multi-Cloud Platform
Моделирование и анализ информационных систем
adaptive firewall
software-defined network
multi-cloud platforms
neural network
network function virtualization
cyber security
title Development and Study of Algorithms for the Formation of Rules for Network Security Nodes in the Multi-Cloud Platform
title_full Development and Study of Algorithms for the Formation of Rules for Network Security Nodes in the Multi-Cloud Platform
title_fullStr Development and Study of Algorithms for the Formation of Rules for Network Security Nodes in the Multi-Cloud Platform
title_full_unstemmed Development and Study of Algorithms for the Formation of Rules for Network Security Nodes in the Multi-Cloud Platform
title_short Development and Study of Algorithms for the Formation of Rules for Network Security Nodes in the Multi-Cloud Platform
title_sort development and study of algorithms for the formation of rules for network security nodes in the multi cloud platform
topic adaptive firewall
software-defined network
multi-cloud platforms
neural network
network function virtualization
cyber security
url https://www.mais-journal.ru/jour/article/view/1164
work_keys_str_mv AT denisiparfenov developmentandstudyofalgorithmsfortheformationofrulesfornetworksecuritynodesinthemulticloudplatform
AT irinapbolodurina developmentandstudyofalgorithmsfortheformationofrulesfornetworksecuritynodesinthemulticloudplatform
AT vadimatorchin developmentandstudyofalgorithmsfortheformationofrulesfornetworksecuritynodesinthemulticloudplatform