摘要
随着数字政府建设的深入,政务信息系统在质量保障与安全协同方面面临日益突出的挑战。传统基于静态监控和分散式安全策略的方法,已难以支撑系统对高可用与高可信的运行要求。本文提出了一种融合AIOps与DevSecOps的质量安全协同保障模型,构建了涵盖数据采集、异常检测、风险建模和自动响应的闭环机制。模型采用多因子评分策略,并结合图神经网络进行事件关联建模,支持对质量波动与安全风险的跨阶段识别与评估。在真实政务平台数据集上的实验结果表明,该模型在准确率、响应时延及评分一致性方面均显著优于传统方法,具备良好的工程适用性与推广价值。
With the deepening of digital government construction,government information systems are facing increasingly prominent challenges in terms of quality assurance and security coordination.The traditional methods based on static monitoring and distributed security policies have become difficult to support the system’s operational requirements for high availability and high credibility.Therefore,this paper proposes a quality and safety collaborative guarantee model integrating AIOps and DevSecOps,and constructs a closed-loop mechanism covering data collection,anomaly detection,risk modeling and automatic response.The model adopts a multi-factor scoring strategy and combines graph neural networks for event correlation modeling,supporting cross-stage identification and assessment of quality fluctuations and safety risks.The experimental results on the real government affairs platform dataset show that this model is significantly superior to the traditional methods in terms of accuracy,response delay and score consistency,and has good engineering applicability and promotion value.
作者
许鑫
陈戎
鹿洵
XU Xin;CHEN Rong;LU Xun(Shenzhen Information Security Management Center,Shenzhen 518038,China;Shenzhen CEPREI Industry Technology Research Institute Co.,Ltd.,Shenzhen 518055,China)
出处
《电子质量》
2026年第2期70-76,共7页
Electronics Quality
