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Author:

Hashemi, Seyed Mahmood (Hashemi, Seyed Mahmood.) | He, Jingsha (He, Jingsha.) (Scholars:何泾沙)

Indexed by:

EI Scopus

Abstract:

Security is the most important issue in a network system. Administrators can more easily understand threats to the network by using a model. In this paper, we present an approach for modelling a network that considers the benefits of the network as well as its limitations. In our approach, we model the system as an optimization problem, which is solved using three algorithms. As the proposed approach is stochastic, it works very efficiently in a network environment. This paper, presents a mathematical model of the system. Model provides easy comprehend of system. Presented model is based on multi-objective optimization problem. One parameter in the presented model is security and another parameter is user productivity. Security is the most important issue in a network system. Administrators can more easily understand threats to the network by using a model. In this paper, we present an approach for modelling a network that considers the benefits of the network as well as its limitations.

Keyword:

Stochastic systems Multiobjective optimization Optimization Network security

Author Community:

  • [ 1 ] [Hashemi, Seyed Mahmood]School of Software Engineering, Beijing University of Technology, Beijing Engineering Research Center for IoT Software and Systems, China
  • [ 2 ] [He, Jingsha]School of Software Engineering, Beijing University of Technology, Beijing Engineering Research Center for IoT Software and Systems, China

Reprint Author's Address:

  • [hashemi, seyed mahmood]school of software engineering, beijing university of technology, beijing engineering research center for iot software and systems, china

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Related Keywords:

Source :

International Journal of Network Security

ISSN: 1816-353X

Year: 2017

Issue: 4

Volume: 19

Page: 528-536

Cited Count:

WoS CC Cited Count:

SCOPUS Cited Count: 2

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 0

Online/Total:568/5282008
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