识别并检测社交媒体中针对重要人物的协同回复攻击
Coordinated Reply Attacks in Influence Operations: Characterization and Detection
- 构建两个机器学习模型，分别识别被攻击的推文和协同攻击账号
- 分类模型AUC达0.88和0.97，可有效识别攻击行为
- 适合研究网络舆论操控、平台安全与舆情监测的学者和从业者
协同回复攻击是在线影响力操作中的一种策略，用于支持或骚扰特定个体及其受众。尽管其具有显著影响力，但以往研究尚未系统分析或提出检测方法。本研究在推特平台上对这类攻击进行表征分析，发现主要目标为记者、媒体机构、政府官员及政界人士等高影响力个体。我们提出两种监督学习模型：一个用于判断推文是否遭回复攻击，另一个用于判断回复账号是否属于协同攻击。两类模型的AUC得分分别为0.88和0.97，表明攻击账号可被有效识别，且被攻击账号本身可作为影响操作的探测传感器。
原文摘要 · Abstract (English)
Coordinated reply attacks are a tactic observed in online influence operations and other coordinated campaigns to support or harass targeted individuals, or influence them or their followers. Despite its potential to influence the public, past studies have yet to analyze or provide a methodology to detect this tactic. In this study, we characterize coordinated reply attacks in the context of influence operations on Twitter. Our analysis reveals that the primary targets of these attacks are influential people such as journalists, news media, state officials, and politicians. We propose two supervised machine-learning models, one to classify tweets to determine whether they are targeted by a reply attack, and one to classify accounts that reply to a targeted tweet to determine whether they are part of a coordinated attack. The classifiers achieve AUC scores of 0.88 and 0.97, respectively. These results indicate that accounts involved in reply attacks can be detected, and the targeted accounts themselves can serve as sensors for influence operation detection.
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