The rapid development of digital economy has led to the emergence of various
black and shadow internet industries, which pose potential risks that can be
identified and managed through digital risk management (DRM) that uses
different techniques such as machine learning and deep learning. The evolution
of DRM architecture has been driven by changes in data forms. However, the
development of AI-generated content (AIGC) technology, such as ChatGPT and
Stable Diffusion, has given black and shadow industries powerful tools to
personalize data and generate realistic images and conversations for fraudulent
activities. This poses a challenge for DRM systems to control risks from the
source of data generation and to respond quickly to the fast-changing risk
environment. This paper aims to provide a technical analysis of the challenges
and opportunities of AIGC from upstream, midstream, and downstream paths of
black/shadow industries and suggest future directions for improving existing
risk control systems. The paper will explore the new black and shadow
techniques triggered by generative AI technology and provide insights for
building the next-generation DRM system.

本文分析了 AIGC 技术在黑色和灰色互联网产业的上中下游路径中对 DRM 系统的挑战和机遇，探讨了生成式 AI 技术引发的新黑色和灰色技术，并提出了提高现有风险控制系统的未来方向。