传感器网络自适应保护系统结构

A. Basan, E. Basan, O. Peskova, Nikita Sushkin, M. Shulika
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引用次数: 0

摘要

38АдаптивнаясистемазащитысенсорныхсетейотактивныхатакВопросыкибербезопасности。2022. [6]杨建军,杨建军,杨建军,等。传感器网络自适应保护系统的体系结构。8、苏什金9、舒利卡10目的:基于网络物理参数的收集和分析,开发用于异常检测的传感器网络和网络物理系统的自适应保护系统架构。方法:该方法以概率论、数理统计和信息论为基础。原始数据的熵测度和归一化使得数据的统一和异常检测评价成为可能。结果:分析了现有的保护网络物理系统免受外部主动攻击的解决方案。提出了一种用于网络物理系统防护的自适应系统体系结构。作为节点数据采集与分析子系统的一部分,提出了一种用于入侵检测的网络物理参数估计方法。本研究详细分析了四种行为情景下的三个参数变化。即使只有三个参数,您也可以确定攻击与正常行为之间的区别。不仅可以评估参数变化的事实,而且可以评估其变化的程度。同时,节点自主比较自身参数的变化与相邻节点参数的变化,能够识别攻击对相邻节点的影响。科学的新颖性主要在于这样一个事实,即首次开发了一种基于使用熵度量和原始数据规范化来评估系统参数的方法来确定网络物理系统的异常活动,这使得实现对已知和未知攻击的高水平检测成为可能。这种方法也可以有效地用于自治系统。提出了网络物理系统自适应保护系统的原始体系结构,并对其主要组成部分进行了设计。当在分布式系统中实施攻击时,这种开发将允许节点不仅自主地检测异常,而且是分布式的,即检测对相邻节点的影响。
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ARCHITECTURE OF ADAPTIVE PROTECTION SYSTEM FOR SENSOR NETWORK
38Адаптивная система защиты сенсорных сетей от активных атак Вопросы кибербезопасности. 2022. No 6(52) Architecture of AdAptiVe protection system for sensor netWorK Basan A.S.6 , Basan E.S.7 , Peskova O.Yu.8 , Sushkin N.A.9 , Shulika M.G.10 Purpose: Development of the adaptive protection system architecture for sensor networks and cyber-physical systems for anomaly detection based on the collection and analysis of cyber-physical parameters. Method: The method is based on the use of probability theory, mathematical statistics, and information theory. The entropy measure and normalization of the raw data make it possible to unify the data and evaluate it in terms of anomaly detection. Results: The existing solutions for the protection of cyber-physical systems from external active attacks were analyzed. The architecture of an adaptive system for a cyber-physical system protection is proposed. As part of the representation of the node data collection and analysis subsystem, a method for estimating cyber-physical parameters to detect intrusions is proposed. Three parameter changes for four behavioral scenarios were analyzed in detail in this study. Even by three parameters, you can determine the difference between attacks and normal behaviors. It is possible to evaluate not only the fact of parameter change, but also the degree of its change. At the same time, the node autonomously compared changes in its parameters with changes in the parameters of the neighboring node and could identify the impact of the attack on the neighboring node. The scientific novelty primarily consists in the fact that for the first time a method for determining the abnormal activity of a cyber-physical system based on the evaluation of system parameters using a measure of entropy and normalization of raw data has been developed, which makes it possible to achieve a high level of detection of known and unknown attacks. This method can be effectively used also for autonomous systems. The original architecture of the adaptive system for protecting the cyber-physical system is also proposed, its main components are worked out. When implementing an attack in a distributed system, this development will allow the node to detect anomalies not only autonomously, but also distributed, that is, to detect the impact on neighboring nodes.
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