基于神经模糊逻辑的自动化系统信息安全风险评估

A. Aydinyan, O. Tsvetkova
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引用次数: 0

摘要

目标。自动化系统在生产中应用广泛,信息安全是衡量自动化系统可靠性的重要标准。该研究的目的是在威胁的实施可能造成的损失和使用神经模糊逻辑方法降低风险的保护工具的成本之间提供平衡。所建立的模型基于模糊逻辑的应用。获得了综合信息安全风险评估模型,可实际应用于综合分析在各种活动领域中运行的自动化系统组织保护系统的有效性。在语言变量的帮助下,揭示了自动化系统信息安全的风险指标。基于这些指标,从软件状态得到信息安全风险评估;技术支持;信息支持;组织和方法支持;员工的培训和激励水平。该模型的模糊产生规则是为了确定自动化系统信息安全的综合评估,提供了对自动化系统安全水平有重大影响的所有因素的全面考虑。提出的方法的一个特点是评估过程的正规化,减少了形成风险评估时的主观性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Assessment of information security risks of automated system using neuro-fuzzy logic
Objective. Automated systems are widely used in production, and an important criterion for their reliability is information security. The aim of the study is to provide a balance between possible losses as a result of the implementation of threats and the cost of protection tools that reduce risks using neuro-fuzzy logic.Method. The developed model is based on the use of fuzzy logic.Result. A model of integrated information security risk assessment has been obtained, which can be practically applied for a comprehensive analysis of the effectiveness of organizing a protection system for automated systems operating in various fields of activity. The risk indicators of information security of an automated system, described with the help of linguistic variables, are revealed. Based on these indicators, information security risk assessments were obtained from the state of: software; technical support; information support; organizational and methodological support; the level of training and motivation of employees. The fuzzy production rules of the model are formulated to determine the integrated assessment of the information security of an automated system, providing a full account of all factors that have a significant impact on the level of security of an automated system.Conclusions. A feature of the proposed approach is the formalization of the assessment process, reducing the level of subjectivity in the formation of risk assessments.
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