Automatic scam-baiting is an online fraud countermeasure that involves automated systems responding to online fraudsters in order to waste their time and deplete their resources, diverting attackers away from real potential victims. Previous work has demonstrated that text generation systems are capable of engaging with attackers as automatic scam-baiters, but the fluency and coherence of generated text may be a limit to the effectiveness of such systems. In this paper, we report on the results of a month-long experiment comparing the effectiveness of two ChatGPT-based automatic scam-baiters to a control measure. Within our results, with engagement from over 250 real email fraudsters, we find that ChatGPT-based scam-baiters show a marked increase in scammer response rate and conversation length relative to the control measure, outperforming previous approaches. We discuss the implications of these results and practical considerations for wider deployment of automatic scam-baiting.

翻译：自动反钓鱼诱骗是一种在线欺诈对抗措施，涉及自动化系统与网络诈骗者交互，以消耗其时间和资源，从而将攻击者从真实潜在受害者处引开。先前研究表明，文本生成系统能够作为自动反诱骗程序与诈骗者互动，但生成文本的流畅性和连贯性可能限制了这类系统的有效性。本文报告了一项为期一个月的实验结果，比较了两种基于ChatGPT的自动反诱骗程序与对照措施的效果。在超过250名真实电子邮件诈骗者参与的结果中，我们发现基于ChatGPT的反诱骗程序在诈骗者回复率和对话长度方面较对照措施显著提升，优于以往方法。我们讨论了这些结果的启示以及更广泛部署自动反诱骗的实际考量。