# Machine Learning-Based Detection of Pump-and-Dump Schemes in Real-Time

arXiv: https://arxiv.org/abs/2412.18848 · HTML: https://mlsanity.com/paper/2412.18848/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 25 Dec 2024.

## Built on by (most cited first, 2 of 2)

- [DAO-enabled decentralized physical AI: A new paradigm for human-machine collaboration](https://mlsanity.com/paper/2605.04522/) (2026)
- [PumpSense: Real-Time Detection and Target Extraction of Crypto Pump-and-Dumps on Telegram](https://mlsanity.com/paper/2605.09431/) (2026)

## Abstract (arXiv)

Cryptocurrency markets often face manipulation through prevalent pump-and-dump (P&D) schemes, where self-organized Telegram groups, some exceeding two million members, artificially inflate target cryptocurrency prices. These groups sell premium access to inside information, worsening information asymmetry and financial risks for subscribers and all investors. This paper presents a real-time prediction pipeline to forecast target coins and alert investors to possible P&D schemes. In a Poloniex case study, the model accurately identified the target coin among the top five from 50 random coins in 24 out of 43 (55.81%) P&D events. The pipeline uses advanced natural language processing (NLP) to classify Telegram messages, identifying 2,079 past pump events and detecting new ones in real-time.