发表机构
Electronics and Telecommunications Research Institute (ETRI); University of Science and Technology (UST)（电子通信研究院（ETRI）; 科学技术大学（UST））
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
提出Vishing-Tactics-Bench基准，基于态势感知框架将语音钓鱼防御转为伤害预测，定义利用轨迹预测协议，通过战术轨迹支持干预选择并实现早期预警。
AI 中文摘要
语音钓鱼（vishing）实时展开；当通话结束并可以进行事后分类时，伤害已经造成。更具可操作性的问题是，正在进行的通话在战术上正朝着哪种具体伤害（信息收集或财务利用）发展。我们提出了Vishing-Tactics-Bench，一个基于Endsley态势感知（SA）框架的基准，将语音钓鱼防御从事后欺诈分类重新定义为伤害预测：在每一轮预测通话是否会达到任一最终伤害。我们将MITRE ATT&CK适配为语音钓鱼的6战术分类法（Vishing-Tactics），并为5,645个合成中文通话中的35,340条诈骗者话语标注了标签。我们定义了利用轨迹预测，一种针对两种最终伤害的生存风格协议，包含三个指标：AP@k、C-index和散度误差。从马尔可夫启发式到微调LLM的基线表明，战术轨迹可作为通话战术状态的可解释表示，支持针对特定伤害的预测，进而可用于下游干预选择应用；在严格误报预算下的分层提前时间分析进一步确定了通话中轨迹信号产生早期预警的时间点。
英文摘要
Voice phishing (vishing) unfolds in real time; by the time a call has ended and post-hoc classification is possible, the harm has already been done. The more actionable question is which concrete harm (Information Gathering or Financial Exploitation) an ongoing call is tactically progressing toward. We present Vishing-Tactics-Bench, a benchmark grounded in Endsley's situation-awareness (SA) framework that recasts vishing defense from after-the-fact fraud classification to harm projection: predicting at each turn whether the call will reach either terminal harm. We adapt MITRE ATT&CK to vishing as a 6-tactic taxonomy (Vishing-Tactics) and label 35,340 scammer utterances across 5,645 synthetic Chinese calls. We define Exploitation Trajectory Forecasting, a survival-style protocol over the two terminal harms with three metrics: AP@k, C-index, and divergence error. Baselines ranging from a Markov heuristic to fine-tuned LLMs show that the tactical trajectory serves as an interpretable representation of the call's tactical state, supporting harm-specific forecasting, which can then be used for the downstream application of intervention selection; a stratified lead-time analysis at a tight false-alarm budget further identifies at what point in a call the trajectory signal yields early warning.
Comments16 pages, 3 figures. Accepted to Findings of EMNLP 2026
