Technical Support Scam (TSS) is a cybercrime that not only elicits the trust of a user but swindles their property. To detect TSS attacks in malicious samples, an intelligent TSS-aware system, called the AI@TSS system, was proposed in the study. The proposed AI@TSS system was built by the LightGBM algorithm with different kinds of features. In the study, 8263 malicious web page samples and 8263 TSS web page samples were collected and 42 features are defined for modeling the AI@TSS system. The performance analysis results demonstrate that the AI@TSS system reaches the accuracy and precision of 98% and 100%, respectively. The comparison shows superior to the existing detection methods, with 2.16% and 3.48% improvement in accuracy and precision.

技术支持诈骗 (TSS) 是一种网络犯罪，不仅会引起用户的信任，还会诈骗他们的财产。为了检测恶意样本中的 TSS 攻击，研究中提出了一种智能 TSS 感知系统，称为 AI@TSS 系统。所提出的 AI@TSS 系统是由具有不同类型特征的 LightGBM 算法构建的。在研究中，收集了 8263 个恶意网页样本和 8263 个 TSS 网页样本，并定义了 42 个特征用于建模 AI@TSS 系统。性能分析结果表明，AI@TSS系统的准确率和准确率分别达到了98%和100%。对比表明优于现有的检测方法，准确度和精密度分别提高了 2.16% 和 3.48%。