OPTIMIZATION OF PLACEMENT OF INFORMATION PROTECTION MEANS BASED ON THE APPLICATION OF A GENETIC ALGORITHM

V. Lakhno, Volodimir Maliukov, Larysa Komarova, D. Kasatkin, T.Yu. Osypova, Y. Chasnovskyi
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Abstract

the article considers the possibilities of modifying the genetic algorithm (GA) for solving the problem of selecting and optimizing the configurations of information protection means (IPR) for security circuits of information and communication systems (ICS). The scientific novelty of the work lies in the fact that in GA, as criteria for optimizing the composition of IPR, it is proposed to use the total value of risks from loss of information, as well as the integral indicator of IPR and cost indicators for each class of IPR. The genetic algorithm in the task of optimizing the selection of the composition of the IPR for ICS is considered as a variation of the problem associated with multiple selection. In such a statement, the optimization of the placement of IPR along the contours of ICS protection is considered as a modification of the combinatorial problem about the backpack. The GA used in the computing core of the decision support system (DSS) differs from the standard GA. As part of the GA modification, chromosomes are presented in the form of matrices, the elements of which are numbers that correspond to the numbers of the IPR in the ICS nodes. In the process of GA modification, k-point crossover was applied. The fitness function is represented as the sum of efficiency coefficients. At the same time, in addition to the traditional absolute indicators of the effectiveness of IPR, the total value of risks from loss of information, as well as cost indicators for each class of IPR are taken into account. The practical value of the research lies in the implementation of the DSS based on the proposed modification of the GA. Computational experiments on the selection of a rational software algorithm for the implementation of the model were performed. It is shown that the implementation of GA in DSS allows to speed up the search for optimal options for the placement of cyber security means (CS) for ICS by more than 25 times. This advantage allows not only to perform a quick review of various options of hardware and software IPR and their combinations for ICS, but also to further combine the proposed algorithm with existing models and algorithms for optimizing the composition of ICS cyber security circuits. Potentially, such a combination of models and algorithms will provide an opportunity to quickly rebuild ICS protection, adjusting its profiles in accordance with new threats and classes of cyberattacks.
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基于应用遗传算法的信息保护手段布局优化
本文考虑了改进遗传算法解决信息通信系统(ICS)安全电路中信息保护手段(IPR)配置选择和优化问题的可能性。本文的科学新颖之处在于,在遗传算法中,提出了利用信息丢失风险的总价值、知识产权的积分指标和每一类知识产权的成本指标作为优化知识产权构成的标准。遗传算法在优化ICS知识产权组合选择问题中的应用被认为是多选择问题的一种变体。在这种情况下,知识产权沿ICS保护轮廓的优化放置被认为是对背包组合问题的修正。决策支持系统(DSS)计算核心中使用的遗传算法不同于标准遗传算法。作为GA修改的一部分,染色体以矩阵的形式呈现,矩阵的元素是与ICS节点中IPR的数字相对应的数字。在遗传算法修正过程中,采用k点交叉。适应度函数表示为效率系数的和。同时,除了传统的知识产权有效性的绝对指标外,还考虑了信息丢失风险的总价值,以及每一类知识产权的成本指标。本研究的实用价值在于基于改进遗传算法的决策支持系统的实现。通过计算实验,选择合理的软件算法实现该模型。研究表明,在决策支持系统中实施遗传算法可以将寻找网络安全手段(CS)的最佳选择的速度提高25倍以上。这一优势不仅允许对ICS的各种硬件和软件IPR及其组合进行快速审查,而且还可以进一步将所提出的算法与现有模型和算法相结合,以优化ICS网络安全电路的组成。潜在地,这种模型和算法的组合将为快速重建ICS保护提供机会,并根据新的威胁和网络攻击类别调整其配置文件。
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