Integration strategy of RTU functional security and information security based on two-level game and discrete particle swarm optimization
|更新时间:2026-10-15
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Integration strategy of RTU functional security and information security based on two-level game and discrete particle swarm optimization
Vol. 63, Issue 10, (2026)
作者机构:
1. 南方电网科学研究院有限责任公司
2. 广东省电力系统网络安全企业重点实验室,广州,510663
3. 云南电网有限责任公司信息中心,云南省,昆明
4. 哈尔滨工业大学电气工程及自动化学院
作者简介:
基金信息:
DOI:
CLC:
Published:2026
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Hong Chao, Xiao Peng, Li Zhongwei, et al. Integration strategy of RTU functional security and information security based on two-level game and discrete particle swarm optimization[J]. 2026, 63(10).
DOI:
Hong Chao, Xiao Peng, Li Zhongwei, et al. Integration strategy of RTU functional security and information security based on two-level game and discrete particle swarm optimization[J]. 2026, 63(10).DOI:
Integration strategy of RTU functional security and information security based on two-level game and discrete particle swarm optimization
With the continuous improvement of the scale and openness of smart grid
power monitoring devices such as remote terminal units (RTU) have put forward an urgent need for the integration of functional security and information security (functional safety and information security integration) in ensuring reliability and preventing network attacks. However
the existing two security integration strategies rely heavily on experience driven stacking
lacking systematic integration and unified quantitative evaluation
making it difficult to achieve coordination and balance between security benefits and resource costs in resource constrained environments. Therefore
this paper proposes two security integration strategy based on two-level game and discrete particle swarm optimization
where each security unit independently selects protective measures under resource constraints through a non-cooperative game model. By using a cooperative game model
the ability to protect security measures is considered in conjunction with three types of resource constraints. The discrete particle swarm algorithm is optimized to solve the cooperative game model and obtain the optimal combination of security protection measures. The test results on a certain RTU demonstrate that the proposed method achieves a central processing unit occupancy rate of 20% and read-only memory usage of 12 MB for the combination of security protection measures
with a comprehensive protection score of 65 points. The proposed strategy can efficiently coordinate security performance and hardware overhead in resource-constrained RTU environments
effectively addressing the limitations of existing schemes and providing an efficient and secure solution. The presented two-level game plus optimization model exhibits superior strategy effectiveness and resource adaptability.