Sequence-Based Target Coin Prediction for Cryptocurrency Pump-and-Dump

• URL: http://arxiv.org/abs/2204.12929v2
• Date: Mon, 3 Apr 2023 16:19:11 GMT
• Title: Sequence-Based Target Coin Prediction for Cryptocurrency Pump-and-Dump
• Authors: Sihao Hu, Zhen Zhang, Shengliang Lu, Bingsheng He, Zhao Li
• Abstract summary: This paper focuses on predicting the pump probability of all coins listed in the target exchange before a scheduled pump time. We conduct a comprehensive study of the latest 709 P&D events organized in Telegram from Jan. 2019 to Jan. 2022. We develop a novel sequence-based neural network, dubbed SNN, which encodes a channel's P&D event history into a sequence representation.
• Score: 39.06710188537909
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: With the proliferation of pump-and-dump schemes (P&Ds) in the cryptocurrency market, it becomes imperative to detect such fraudulent activities in advance to alert potentially susceptible investors. In this paper, we focus on predicting the pump probability of all coins listed in the target exchange before a scheduled pump time, which we refer to as the target coin prediction task. Firstly, we conduct a comprehensive study of the latest 709 P&D events organized in Telegram from Jan. 2019 to Jan. 2022. Our empirical analysis reveals some interesting patterns of P&Ds, such as that pumped coins exhibit intra-channel homogeneity and inter-channel heterogeneity. Here channel refers a form of group in Telegram that is frequently used to coordinate P&D events. This observation inspires us to develop a novel sequence-based neural network, dubbed SNN, which encodes a channel's P&D event history into a sequence representation via the positional attention mechanism to enhance the prediction accuracy. Positional attention helps to extract useful information and alleviates noise, especially when the sequence length is long. Extensive experiments verify the effectiveness and generalizability of proposed methods. Additionally, we release the code and P&D dataset on GitHub: https://github.com/Bayi-Hu/Pump-and-Dump-Detection-on-Cryptocurrency, and regularly update the dataset.

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