Affiliations: [a] Department of Computer Science and Information Systems, Bradley University, Peoria, IL, USA | [b] Plekhanov Russian University of Economics, Moscow, Russia | [c] Institute of Management of Education of Russian Academy of Education, Bauman Moscow State Technical University, Moscow, Russia
Correspondence:
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Corresponding author: Alexander Uskov, Department of Computer Science and Information Systems, Bradley University, 1501 West Bradley Avenue, Peoria, IL 61625, USA. Tel.: +1 309 677 2460; Fax: +1 309 677 4504; E-mail:auskov@bradley.edu
Abstract: Optimal design of IPsec-based virtual private networks
(VPN), in general, depends on multiple factors and parameters, such as the
VPN's architectural model, hardware and software setups and the technical
platform solutions, network topology models, modes of the tunnel's
operation, levels of the Open Systems Interconnection (OSI) model,
encryption/decryption algorithms, modes of cipher operation, security
protocols, security associations and key management techniques, connectivity
modes, parameters of security algorithms, computer architectures, the number
of tunnels in the VPN, and other factors. This paper presents an innovative
approach to using methods of linear programming with risks to solve a multi
objective optimization problem of VPN design. In particular, it describes
the proposed conceptual VPN design model, VPN information security space,
index of effectiveness for multi objective optimization, a new
classification of scales, a system-based approach to risks and mathematical
modeling of a risk, a hierarchy of scripts and a theorem of description of
passwords, VPN design optimization process and particular procedures, sets
of legal and illegal VPN design methods, and a VPN design optimization
algorithm based on multi objective optimization by linear programming with
risks models. The proposed and developed VPN design optimization algorithm
was tested by developing specific VPN design methods for various types of
VPN users.
Keywords: Multi objective optimization, linear programing models, risks, VPN design
