Network attacks identification method of relay protection devices communication system based on Fp-Growth algorithm

Honghui Gao, Zebing Shi, Fangying Wu, Jiang Yu, Quan Xu, Hongzi He, Zhihua Huang
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Abstract

In order to ensure the stable operation of relay protection device and identify untrusted data code attacks, this paper proposes a network attacks identification method for relay protection devices communication system based on frequent pattern-growth(FP-Growth) algorithm. Firstly, the transmission model of the communication system of the relay protection device is analyzed. The physical side and the communication side of the relay protection device are monitored through the real-time simulation platform to obtain the original data. Then, the original data are discretely quantized and encoded to generate the abnormal event sequence. Then, FP-Growth algorithm is used to analyze the association of the event sequence to obtain the longest and most frequent sequences. The new attacks categories and fault points are compared by the existing frequent sequence characteristics to determine the type of network attacks or the location of fault points, so as to realize the identification of malicious code attacks, and provide a theoretical basis for the application of trusted technology.
基于Fp-Growth算法的继电保护设备通信系统网络攻击识别方法
为了保证继电保护设备的稳定运行和识别不可信数据码攻击,本文提出了一种基于频繁模式增长(FP-Growth)算法的继电保护设备通信系统网络攻击识别方法。首先,分析了继电保护装置通信系统的传输模型。通过实时仿真平台对继电保护装置的物理侧和通信侧进行监控,获取原始数据。然后,对原始数据进行离散量化编码,生成异常事件序列。然后,利用FP-Growth算法对事件序列进行关联分析,得到最长和最频繁的序列。将新的攻击类别和故障点与现有的频繁序列特征进行比较,确定网络攻击的类型或故障点的位置,从而实现对恶意代码攻击的识别,为可信技术的应用提供理论依据。
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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