基于群集智能算法的工业互联网防御脆弱点识别  

Identification of vulnerability and weakness in industrial Internet defense based on cluster intelligence algorithm

作　　者：陈康平 于秋玲 卢芳 CHEN Kangping;YU Qiuling;LU Fang(China Southern Power Grid Digital Power Grid Group Co.,Ltd.,Guangzhou 510663,China)

机构地区：[1]南方电网数字电网集团有限公司,广东广州510663

出　　处：《电子设计工程》2025年第5期152-156,161,共6页Electronic Design Engineering

基　　金：南方电网数字电网集团有限公司科技项目(2020004GX0021)。

摘　　要：基于工业互联网防御脆弱点多且识别结果不精准的目的,采用了基于群集智能算法的工业互联网防御脆弱点识别方法。结合群集智能算法的脆弱点的识别流程,并将群集智能视为一种改进的蚂蚁算法,通过计算蚂蚁转移的概率和信息素浓度,循环遍历直至达到最大周期数,获取最短识别路径,并设计判决门限确定脆弱点。由实验结果可知,该方法在攻击方式一、二下识别到的防御脆弱点分别为16个和21个,与真实情况一致,精准识别效果较好,具有较强的实用性。Based on the goal of multiple vulnerable points in industrial internet defense and inaccurate identification results,a cluster intelligence algorithm based method for identifying vulnerable points in industrial internet defense was adopted.Combining the identification process of vulnerability points in swarm intelligence algorithms,and considering swarm intelligence as an improved ant algorithm,it calculates the probability of ant transfer and pheromone concentration,iterates until the maximum number of cycles is reached,obtains the shortest identification path,and designs a decision threshold to determine the vulnerability.From the experimental results,it can be seen that this method identifies 16 and 21 defense vulnerabilities in attack modes 1 and 2,respectively,which are consistent with the real situation.The accurate recognition effect is good,and it has strong practicality.

关 键 词：群集智能算法 工业互联网 防御脆弱点识别 改进蚂蚁算法 信息素 

分 类 号：TN06[电子电信—物理电子学]