基于告警增量分析的攻击场景实时重构方法

赵新建; 汤慧敏; 陈石; 张玉健; 张颂; 程光

doi:10.11959/j.issn.2096-109x.AQ25274

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基于告警增量分析的攻击场景实时重构方法

学术论文 | 更新时间：2026-05-11

- 基于告警增量分析的攻击场景实时重构方法
- Real-time attack scenario reconstruction method based on incremental alert analysis
- 网络与信息安全学报 2026年12卷第2期页码：143-155
- 作者机构：
  
  1.国网江苏省电力有限公司信息通信分公司，江苏南京 210024
  2.东南大学网络空间安全学院，江苏南京 211189
- 作者简介：
  
  [ "赵新建（1987- ），男，国网江苏省电力有限公司信息通信分公司高级工程师，主要研究方向为电力数字化和网络安全。" ]
  [ "汤慧敏（2000- ），女，东南大学硕士生，主要研究方向为网络安全和攻击溯源。" ]
  [ "陈石（1995- ），男，国网江苏省电力有限公司信息通信分公司工程师，主要研究方向为电力数字化和网络安全。" ]
  [ "张玉健（1984- ），男，东南大学副教授，主要研究方向为分布式系统和系统安全。" ]
  [ "张颂（1996- ），男，国网江苏省电力有限公司信息通信分公司工程师，主要研究方向为电力数字化和网络安全。" ]
  [ "程光（1973- ），男，东南大学教授，主要研究方向为流量分析和网络架构。" ]
- 基金信息：
  
  国网江苏省电力有限公司科技项目(J2024086)
- DOI：10.11959/j.issn.2096-109x.AQ25274
  中图分类号： TP393
- 收稿：2025-11-29，
  
  修回：2026-03-24，
  
  录用：2026-03-24，
  
  纸质出版：2026-04-25
- 稿件说明：
移动端阅览
赵新建, 汤慧敏, 陈石, 等. 基于告警增量分析的攻击场景实时重构方法[J]. 网络与信息安全学报, 2026, 12(2): 143-155.

Zhao Xinjian, Tang Huimin, Chen Shi, et al. Real-time attack scenario reconstruction method based on incremental alert analysis[J]. Chinese Journal of Network and Information Security, 2026, 12(2): 143-155.
赵新建, 汤慧敏, 陈石, 等. 基于告警增量分析的攻击场景实时重构方法[J]. 网络与信息安全学报, 2026, 12(2): 143-155. DOI： 10.11959/j.issn.2096-109x.AQ25274.

Zhao Xinjian, Tang Huimin, Chen Shi, et al. Real-time attack scenario reconstruction method based on incremental alert analysis[J]. Chinese Journal of Network and Information Security, 2026, 12(2): 143-155. DOI： 10.11959/j.issn.2096-109x.AQ25274.

摘要

面对日益复杂的多阶段、长周期网络攻击，安全事件常表现出跨时空域的交织关联。攻击场景重构能够有效支撑溯源取证和威胁发现，然而现有在攻击结束后基于全量告警数据分析的方法，存在结果滞后和效率低等问题。为此，针对告警信息的增量更新和全局视角存在矛盾问题，提出了基于时间窗口的增量式攻击场景重构方法。该方法的主要技术创新如下：①通过预处理和时间窗口划分，实现告警数据的规范化表达和分析规模的有效控制；②针对单窗口增量更新数据，以目标资产为中心构建攻击告警图并挖掘频繁1-项集，在此基础上通过图遍历策略生成并筛选所有可能攻击路径；③针对多个窗口的全局视角数据，提出一种攻击路径融合算法对已有路径和增量路径进行关联，实现攻击场景的全局重构。在开源和真实数据集上的实验结果表明，所提方法能够有效实现攻击场景重构，同时相比全量分析方法显著降低了计算复杂度，在增量场景下保持了稳定的处理性能。

Abstract

In the face of increasingly complex multi-stage and long-term cyber attacks

security events often exhibit interconnections across both temporal and spatial domains. Attack scenario reconstruction plays a crucial role in supporting traceability

forensics

and threat discovery. However

existing methods that rely on analyzing full alert data after an attack has concluded suffer from issues such as delayed results and efficiency bottlenecks. To address the inherent tension between incremental alert updates and a global perspective

an incremental attack scenario reconstruction method based on time window was proposed. The key technical innovations of the proposed method were as follows: ①Through preprocessing and time-window partitioning

normalized representation of alert data was achieved while effectively controlling the analysis scale; ②For incrementally updated data within a single window

an attack alert graph was constructed centered on target assets as well as mining frequent 1-itemsets

followed by the use of a graph traversal strategy to generate and filter all possible attack paths; ③For multi-window data from a global perspective

an attack path fusion algorithm was introduced to correlate historical paths with incremental paths

enabling global reconstruction of the attack scenario. Experimental results on both open-source and real-world datasets demonstrate that the proposed method effectively achieved attack scenario reconstruction while significantly reducing computational complexity compared to full analysis method

maintaining stable processing performance in incremental scenarios.

关键词

Keywords

references

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