Malware Correlation Monitoring in Computer Networks of Promising Smart Grids

A. Kuznetsov, S. Kavun, Oleksii Smirnov, V. Babenko, O. Nakisko, K. Kuznetsova
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引用次数: 18

Abstract

The structure and features of the construction for intrusion detection and prevention network systems, as well as methods for the correlation analysis of telecommunication traffic in computer systems and networks are considered. Method for detecting malicious software based on the correlation analysis of network traffic is proposed. In particular, it is shown that using the results of statistical studies of time series on the basis of calculating the difference of correlation integrals (BDS-testing) allows to detect the malicious software traffic to improve the computer networks security of promising Smart Grids systems.
有发展前景的智能电网计算机网络中的恶意软件相关性监测
讨论了入侵检测和防御网络系统的结构和特点,以及计算机系统和网络中通信流量的相关性分析方法。提出了一种基于网络流量相关性分析的恶意软件检测方法。特别是,在计算相关积分差(bds测试)的基础上,利用时间序列的统计研究结果可以检测恶意软件流量,从而提高有发展前景的智能电网系统的计算机网络安全性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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