太赫兹科学与电子信息学报2025，Vol.23Issue(2)：175-181,7.DOI:10.11805/TKYDA2023276
电力物联网终端漏洞关联挖掘优化算法设计
Design of optimization algorithm for vulnerability correlation mining of power Internet of Things terminals
王健 1付志博 1农彩勤 1刘家豪 1许伟杰1
作者信息
- 1. 南方电网数字电网集团信息通信科技有限公司,广东 广州 510670
- 折叠
摘要
Abstract
Affected by the complexity of the power Internet of Things(IoT)and the stealth of terminal vulnerabilities,the traditional vulnerability correlation mining methods currently in use exhibit local biases in correlation feature parameters.This leads to insufficient overall mining scale and low global optimization efficiency of the algorithms,which severely impacts the normal operation of power IoT terminals.To address the aforementioned issues,starting from the structural characteristics of IoT,a black-box genetic algorithm is introduced.By completing the global parameter reconstruction and optimization of the overall mining method through four parts:power IoT terminal status perception,terminal vulnerability correlation mining rule generation,introduction of black-box genetic algorithm parameters,and terminal vulnerability correlation mining,the accuracy and scale of mining are enhanced.Simulation tests indicate that the mining curve values of the proposed method are relatively large,and the mean deviation index difference is 0.1.This demonstrates that the black-box genetic algorithm has high feasibility and effectiveness in the mining of security vulnerabilities in power IoT terminals,and the mining stability is sufficient to meet the current terminal vulnerability mining task requirements.关键词
黑盒遗传算法/电力物联网/终端漏洞/关联挖掘Key words
black box genetic algorithm/power Internet of Things/terminal vulnerability/association mining分类
信息技术与安全科学引用本文复制引用
王健,付志博,农彩勤,刘家豪,许伟杰..电力物联网终端漏洞关联挖掘优化算法设计[J].太赫兹科学与电子信息学报,2025,23(2):175-181,7.
