论文标题
加密泵和转储检测通过深度学习技术
Crypto Pump and Dump Detection via Deep Learning Techniques
论文作者
论文摘要
尽管加密货币本身在过去十年中经历了惊人的收养率，但加密货币欺诈检测是一个严重研究的问题领域。在有关加密货币的所有欺诈活动中，泵和转储方案是最常见的。尽管已经对股票市场上的这类骗局进行了一些研究，但缺乏标记的股票数据和加密货币空间所特有的波动性限制了研究对股票市场的适用性对这个问题领域的适用性。此外，迄今为止，在这个空间中唯一的工作是统计本质上是统计的，或者一直关注经典的机器学习模型，例如随机林木。我们提出了两个现有神经网络体系结构在此问题域中的新颖应用，并表明深度学习解决方案可以大大优于加密货币的所有其他现有泵和转储检测方法。
Despite the fact that cryptocurrencies themselves have experienced an astonishing rate of adoption over the last decade, cryptocurrency fraud detection is a heavily under-researched problem area. Of all fraudulent activity regarding cryptocurrencies, pump and dump schemes are some of the most common. Though some studies have been done on these kinds of scams in the stock market, the lack of labelled stock data and the volatility unique to the cryptocurrency space constrains the applicability of studies on the stock market toward this problem domain. Furthermore, the only work done in this space thus far has been either statistical in nature, or has been concerned with classical machine learning models such as random forest trees. We propose the novel application of two existing neural network architectures to this problem domain and show that deep learning solutions can significantly outperform all other existing pump and dump detection methods for cryptocurrencies.
