Arjun Arunasalam (Purdue University), Andrew Chu (University of Chicago), Muslum Ozgur Ozmen (Purdue University), Habiba Farrukh (University of California, Irvine), Z. Berkay Celik (Purdue University)

The impact of e-commerce on today’s society is a global phenomenon. Given the increased demand for online purchases of items, e-commerce platforms often defer item sales to third-party sellers. A number of these sellers are dropshippers, sellers acting as middlemen who fulfill their customers’ orders through third-party suppliers. While this allows customers to access more products on e-commerce sites, we uncover that abusive dropshippers, who exploit the standard permitted dropshipping model, exist, deceiving customers, and damaging other e-commerce sellers. In this paper, we present the first comprehensive study on the characterization of abusive dropshippers and uncover harmful strategies they use to list items and evade account suspension on e-commerce marketplaces. We crawled the web to discover online forums, instructional material, and software used by the abusive dropshipping community. We inductively code forum threads and instructional material and read software documentation, installing when possible, to create an end-to-end lifecycle of this abuse. We also identify exploitative strategies abusive dropshippers use to ensure persistence on platforms. We then interviewed six individuals experienced in e-commerce (legal consultants and sellers) and developed an understanding of how abusive dropshipping harms customers and sellers. Through this, we present five characteristics that warrant future investigation into automated detection of abusive dropshippers on e-commerce platforms. Our efforts present a comprehensive view of how abusive dropshippers operate and how sellers and consumers interact with them, providing a framework to motivate future investigations into countering these harmful operations.

View More Papers

Understanding the Implementation and Security Implications of Protective DNS...

Mingxuan Liu (Zhongguancun Laboratory; Tsinghua University), Yiming Zhang (Tsinghua University), Xiang Li (Tsinghua University), Chaoyi Lu (Tsinghua University), Baojun Liu (Tsinghua University), Haixin Duan (Tsinghua University; Zhongguancun Laboratory), Xiaofeng Zheng (Institute for Network Sciences and Cyberspace, Tsinghua University; QiAnXin Technology Research Institute & Legendsec Information Technology (Beijing) Inc.)

Read More

DeGPT: Optimizing Decompiler Output with LLM

Peiwei Hu (Institute of Information Engineering, Chinese Academy of Sciences, Beijing, China), Ruigang Liang (Institute of Information Engineering, Chinese Academy of Sciences, Beijing, China), Kai Chen (Institute of Information Engineering, Chinese Academy of Sciences, China)

Read More

Securing the Satellite Software Stack

Samuel Jero (MIT Lincoln Laboratory), Juliana Furgala (MIT Lincoln Laboratory), Max A Heller (MIT Lincoln Laboratory), Benjamin Nahill (MIT Lincoln Laboratory), Samuel Mergendahl (MIT Lincoln Laboratory), Richard Skowyra (MIT Lincoln Laboratory)

Read More