用AI分析走私象牙上的手写标记,帮破获跨国盗猎网络
AI-Driven Detection and Analysis of Handwriting on Seized Ivory: A Tool to Uncover Criminal Networks in the Illicit Wildlife Trade
- 用AI自动提取6085张象牙照片中的1.7万处手写标记
- 发现184种重复出现的签名标记,20个跨多起案件出现
- 为缺乏基因数据时提供低成本、可扩展的犯罪链证据
跨国象牙贸易持续导致非洲大象数量下降,而走私网络难以被瓦解。执法部门查获的象牙上常带有走私者留下的遗传信息和手写标记,这些信息可追溯源头并建立货物关联。过去20年,象牙DNA分析已能确定偷猎地点并连接多批货物,但基因数据成本高且难以获取。相比之下,手写标记易拍照却极少被记录分析。本文提出一套基于AI的流水线,用于提取和分析查获象牙上的手写标记。研究收集了2014至2019年间八次大规模缉获的6,085张照片,通过目标检测模型提取出超过17,000个独立标记,并利用先进AI工具进行标注与描述。识别出184种反复出现的“签名标记”,其中20个出现在多个缉获案件中,建立了跨案走私链条。该方法在其他数据缺失时补充调查缺口,展示了AI在野生动物法医学中的变革潜力,并为整合手写分析打击有组织野生动物犯罪提供了实践路径。
原文摘要 · Abstract (English)
The transnational ivory trade continues to drive the decline of elephant populations across Africa, and trafficking networks remain difficult to disrupt. Tusks seized by law enforcement officials carry forensic information on the traffickers responsible for their export, including DNA evidence and handwritten markings made by traffickers. For 20 years, analyses of tusk DNA have identified where elephants were poached and established connections among shipments of ivory. While the links established using genetic evidence are extremely conclusive, genetic data is expensive and sometimes impossible to obtain. But though handwritten markings are easy to photograph, they are rarely documented or analyzed. Here, we present an AI-driven pipeline for extracting and analyzing handwritten markings on seized elephant tusks, offering a novel, scalable, and low-cost source of forensic evidence. Having collected 6,085 photographs from eight large seizures of ivory over a 6-year period (2014-2019), we used an object detection model to extract over 17,000 individual markings, which were then labeled and described using state-of-the-art AI tools. We identified 184 recurring "signature markings" that connect the tusks on which they appear. 20 signature markings were observed in multiple seizures, establishing forensic links between these seizures through traffickers involved in both shipments. This work complements other investigative techniques by filling in gaps where other data sources are unavailable. The study demonstrates the transformative potential of AI in wildlife forensics and highlights practical steps for integrating handwriting analysis into efforts to disrupt organized wildlife crime.
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