# Attention Paper: How Generative AI Reshapes Digital Shadow Industry?

arXiv: https://arxiv.org/abs/2305.18346 · HTML: https://mlsanity.com/paper/2305.18346/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 14 of its 28 references that are in the map.
- First posted on arXiv 26 May 2023.

## Builds on (most cited first, 14 of 14)

- [LLaMA: Open and Efficient Foundation Language Models](https://mlsanity.com/paper/2302.13971/) (2023)
- [BART: Denoising Sequence-to-Sequence Pre-training for Natural Language Generation, Translation, and Comprehension](https://mlsanity.com/paper/1910.13461/) (2019)
- [HuggingGPT: Solving AI Tasks with ChatGPT and its Friends in Hugging Face](https://mlsanity.com/paper/2303.17580/) (2023)
- [OCR-free Document Understanding Transformer](https://mlsanity.com/paper/2111.15664/) (2021)
- [A Survey on Deep Learning for Named Entity Recognition](https://mlsanity.com/paper/1812.09449/) (2018)
- [Safety Assessment of Chinese Large Language Models](https://mlsanity.com/paper/2304.10436/) (2023)
- [Differentially Private Secure Multi-Party Computation for Federated Learning in Financial Applications](https://mlsanity.com/paper/2010.05867/) (2020)
- [A Pathway Towards Responsible AI Generated Content](https://mlsanity.com/paper/2303.01325/) (2023)
- [To ChatGPT, or not to ChatGPT: That is the question!](https://mlsanity.com/paper/2304.01487/) (2023)
- [Modeling Users' Behavior Sequences with Hierarchical Explainable Network for Cross-domain Fraud Detection](https://mlsanity.com/paper/2201.01004/) (2022)
- [Conclave: secure multi-party computation on big data (extended TR)](https://mlsanity.com/paper/1902.06288/) (2019)
- [A Comprehensive Survey on Machine Learning Techniques and User Authentication Approaches for Credit Card Fraud Detection](https://mlsanity.com/paper/1912.02629/) (2019)
- [Uncovering the Dark Side of Telegram: Fakes, Clones, Scams, and Conspiracy Movements](https://mlsanity.com/paper/2111.13530/) (2021)
- [Crime Scene Re-investigation: A Postmortem Analysis of Game Account Stealers' Behaviors](https://mlsanity.com/paper/1705.00242/) (2017)

## Abstract (arXiv)

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.