基于马尔可夫链的工业系统信息安全事件管理数学模型

IF 0.5 Q4 AUTOMATION & CONTROL SYSTEMS
V. M. Krundyshev, G. A. Markov, I. Yu. Zhukov
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引用次数: 0

摘要

研究了工业物联网(IIoT)系统信息安全保障问题。在研究中发现,在大多数情况下,安全信息和事件管理(SIEM)系统具有配置规则,用于将信息基础设施中的事件关联起来,以全面保护工业企业的信息边界免受外部和内部威胁。在这种情况下,需要创建一个数学装置,以便对SIEM系统的有效性进行准确和客观的估计。研究的结果是,基于已开发的信息安全事件管理数学模型,使用连续时间马尔可夫链形式化了IIoT系统中预防信息安全事件的问题。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Mathematical Model of Information Security Event Management Using a Markov Chain in Industrial Systems

Mathematical Model of Information Security Event Management Using a Markov Chain in Industrial Systems

The problem of ensuring information security in industrial Internet-of-Things (IIoT) systems is considered. In the study, it is found that, in most cases, security information and event management (SIEM) systems with configured rules for correlating events in the information infrastructure are used to protect comprehensively the information perimeter of an industrial enterprise from external and internal threats. In this case, there is a need to create a mathematical apparatus that allows for an accurate and objective estimate of the effectiveness of a SIEM system. As a result of the study, the problem of preventing information security incidents in IIoT systems is formalized based on the developed mathematical model of information security event management using a continuous-time Markov chain.

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来源期刊
AUTOMATIC CONTROL AND COMPUTER SCIENCES
AUTOMATIC CONTROL AND COMPUTER SCIENCES AUTOMATION & CONTROL SYSTEMS-
CiteScore
1.70
自引率
22.20%
发文量
47
期刊介绍: Automatic Control and Computer Sciences is a peer reviewed journal that publishes articles on• Control systems, cyber-physical system, real-time systems, robotics, smart sensors, embedded intelligence • Network information technologies, information security, statistical methods of data processing, distributed artificial intelligence, complex systems modeling, knowledge representation, processing and management • Signal and image processing, machine learning, machine perception, computer vision
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