论文标题
使用统计模式混合比特币交易的检测
Mixing detection on Bitcoin transactions using statistical patterns
论文作者
论文摘要
加密货币引起了很多关注，这主要是因为他们建议的匿名在线支付方式。同时，比特币和其他主要加密货币经历了严重的脱名字攻击。为了解决这些攻击，比特币贡献者引入了称为搅拌机或不倒翁的服务。混合或洗衣服务旨在将匿名性返回网络。在这项研究中，我们解决了由于使用混合服务的使用而导致的比特币和其他加密货币网络中货币足迹的问题。我们设计了跟踪这些服务的交易和地址以及肮脏和清洁货币的地址的方法。由于缺乏标记的数据，我们必须与这些服务进行交易并准备标记的数据。使用这些数据，我们发现了可靠的模式并开发了一种集成算法，以检测比特币网络中的混合交易，混合地址，发送者地址和接收器地址。
Cryptocurrencies gained lots of attention mainly because of the anonymous way of online payment, which they suggested. Meanwhile, Bitcoin and other major cryptocurrencies have experienced severe deanonymization attacks. To address these attacks, Bitcoin contributors introduced services called mixers or tumblers. Mixing or laundry services aim to return anonymity back to the network. In this research, we tackle the problem of losing the footprint of money in Bitcoin and other cryptocurrencies networks caused by the usage of mixing services. We devise methods to track transactions and addresses of these services and the addresses of dirty and cleaned money. Because of the lack of labeled data, we had to transact with these services and prepare labeled data. Using this data, we found reliable patterns and developed an integrated algorithm to detect mixing transactions, mixing addresses, sender addresses, and receiver addresses in the Bitcoin network.
