基于细胞自动机模型电力网络攻击预测技术

doi:10.11959/j.issn.1000-0801.2023099

摘要/Abstract

摘要：

传统电力网络攻击范围预测技术的预测范围不够广，导致电力网络安全性提升效果不明显。为此，提出基于细胞自动机模型的电力网络攻击预测技术。搭建电力细胞自动机模型，将细胞自动机中的细胞看作电力细胞，建立细胞活力值转换规则，将其与攻击者执行攻击概率相结合，预测电力细胞的发展变化。根据中心电力细胞及邻域电力细胞的变化趋势预测电力网络攻击。实验结果表明：在时间因素影响下，提出的基于细胞自动机模型电力网络攻击预测技术的预测攻击节点位置与原始节点基本一致，预测后负荷切除量始终在100 MW以下，本文所提技术的有效性更好。

关键词: 细胞自动机, 电力网络, 攻击概率, 网络信息, 预测模型

Abstract:

The prediction range of the traditional power network attack range prediction technology was not wide enough, resulting in the poor effect of power network security improvement.For this reason, a power network attack prediction technology based on cellular automata model was proposed.A cellular automata model was built, regarding the cells in the cellular automata as power cells, a cell vitality value conversion rule was established and combined with the attack probability of attackers to predict the development and change of power cells.The power network attack was predicted according to the change trend of central power cells and neighboring power cells.The experimental result shows that, under the influence of time factors, the predicted attack node location of the proposed power network attack prediction technology based on cellular automata model is basically consistent with the original node, and the predicted load removal is always below 100 MW, the proposed technology is more effective.

Key words: cellular automata, power network, attack probability, network information, prediction model

中图分类号:

TP391

冶莉娟, 王亦婷, 朱励程. 基于细胞自动机模型电力网络攻击预测技术[J]. 电信科学, 2023, 39(4): 173-179.

Lijuan YE, Yiting WANG, Licheng ZHU. Cellular automata model based power network attack prediction technology[J]. Telecommunications Science, 2023, 39(4): 173-179.

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组件编号	组件信息	CVE编号	漏洞编号	漏洞说明	漏洞利用攻击编号
Z1	工程师站	CVE-2018-3951	D1	HTML代码执行	a1
Z2	Web服务器	CVE-2018-5056	D2	内核中的漏洞允许特权提升	a2
Z3	WinCC操作员站	CVE-2018-2846	D3	数据库SQL注入漏洞	a3
Z4	文件服务器	CVE-2018-4627	D4	组件权限许可和访问控制漏洞	a4
Z5	变频PLC控制器	CVE-2018-0671	D5	模块访问安全绕过漏洞	a5
Z6	气动阀PLC控制器	CVE-2018-0084	D6	远程缓冲区溢出	a6
Z7	数据服务器	CVE-2018-0076	D7	释放后重用漏洞	a7

攻击路径种类	文献[7]方法	文献[8]方法	本文所提方法
path1	376 MW	362 MW	72 MW
path2	232 MW	294 MW	56 MW
path3	352 MW	276 MW	97 MW
path4	328 MW	306 MW	54 MW