A Genetic Approach for Virtual Computer Network Design

Abstract

Abstract. One of possible levels of computer protection may consist in splitting computer networks into logical chunks that are known as virtual computer networks or virtual subnets. The paper considers a novel approach to determine virtual subnets that is based on the given matrix of logic connectivity of computers. The paper shows that the problem considered is related to one of the forms of Boolean Matrix Factorization. It formulates the virtual subnet design task and proposes genetic algorithms as a means to solve it. Basic improvements proposed in the paper are using trivial solutions to generate an initial population, taking into account in the fitness function the criterion of minimum number of virtual subnets, and using columns of the connectivity matrix as genes of chromosomes. Experimental results show the proposed genetic algorithm has high effectiveness.

A role-base approach and a genetic algorithm for VLAN design in large critical infrastructures

“…In all modes, the following values of the main parameters of the genetic algorithm were used: N pop = 200, W cross = 0.1, W mut = 0.01, W gen = W el = 0.5. These values were chosen in such a way that they were equal to similar values of GA parameters used in [5,6]. It provides compatibility of the current experimental results on GA assessment with previous ones.…”

“…In our papers [5,6], the formulation of the optimization problem of the VLAN access control scheme, based on security criteria, was developed, and quite effective genetic algorithms were proposed for solving them. However, with a large dimension of the problem, typical for large critical infrastructures, the speed of these algorithms decreases sharply.…”

“…In the two-dimensional mode of crossover the matrices of the parent chromosomes before crossing are divided into two parts diagonally [5]. The essence of two-dimensional crossover is clearly illustrated in Fig.…”

“…One of these methods that has found wide application for solving similar optimization problems is genetic algorithms. In our previous works, we have shown how genetic algorithms can be successfully applied for solving optimization problems for various access control schemes, including VLANs [3][4][5][6]. However, for large critical infrastructures, the solution of this problem by known methods [5,6] is very laborious due to its large dimension.…”