Statistical data analysis for network infrastructure monitoring to recognize aberrant behavior of system local segments

M. Sukhoparov, Alexander Davydov, I. Lebedev, Nurzhan Bazhayev
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Abstract

Wireless network of low-power devices “Smart Home”, “Internet of things” has been considered. A number of signs of security attacks on behalf of potential information interloper have been identified. We have analyzed the characteristics of a system based on wireless technologies that are obtained as a result of passive surveillance and active polling of devices comprising the network infrastructure. A model is presented for the information security state analysis based on identifying, quantitative, frequency, timing characteristics. In view of the peculiarities of the devices providing network infrastructure, estimation of the information security state is focused on the analysis of the system normal functioning profile, rather than on search of signatures and features of anomalies during various kinds of attacks. An experiment has been disclosed that provides obtaining statistical information about operation of wireless network remote devices where data acquisition for decision-making purposes occurs by comparing statistical signal messages from the leaf nodes in passive and active modes. Experimental results of information onslaught on the standard system have been presented. The proposed model may be used to determine technical characteristics of WLAN ad hoc network devices and to draw recommendations for IS state analysis.
用于网络基础设施监控的统计数据分析,以识别系统本地段的异常行为
无线网络的低功耗设备“智能家居”、“物联网”得到了考虑。许多安全攻击的迹象代表潜在的信息入侵者已被确定。我们分析了一个基于无线技术的系统的特征,该系统是通过被动监视和主动轮询组成网络基础设施的设备而获得的。提出了一种基于识别、定量、频率、时序特征的信息安全状态分析模型。鉴于提供网络基础设施的设备的特殊性,信息安全状态的评估侧重于分析系统的正常功能概况,而不是寻找各种攻击过程中的异常特征和特征。公开了一项实验,通过比较来自叶节点的被动和主动模式的统计信号消息,提供获取用于决策目的的数据采集的无线网络远程设备运行的统计信息。给出了对标准系统进行信息冲击的实验结果。所提出的模型可用于确定WLAN自组织网络设备的技术特征,并为IS状态分析提出建议。
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