Elliptic 的人工智能突破破解了比特币洗钱之谜

区块链分析公司 Elliptic 开发了一种使用深度学习、人工智能技术和海量数据集来识别和跟踪比特币区块链上洗钱活动的方法。这种方法的重点是检测“子图”，即代表已洗钱比特币的交易链，使调查人员能够比监控个人钱包更有效地分析非法活动。

Deciphering the Enigma of Money Laundering on Bitcoin's Blockchain: Elliptic's AI-Powered Breakthrough

破译比特币区块链洗钱之谜：Elliptic 的人工智能突破

The illicit flow of funds through complex financial networks has long posed a formidable challenge to law enforcement agencies, regulators, and financial analysts alike. However, a groundbreaking development from blockchain analysis company Elliptic is poised to revolutionize the detection and tracking of money laundering on the Bitcoin blockchain.

资金通过复杂的金融网络非法流动长期以来给执法机构、监管机构和金融分析师等带来了巨大的挑战。然而，区块链分析公司 Elliptic 的突破性发展有望彻底改变比特币区块链上洗钱的检测和跟踪。

Harnessing the Power of AI and Graph Neural Networks

利用人工智能和图神经网络的力量

Elliptic's innovative approach leverages a deep learning model, state-of-the-art AI techniques, and a massive dataset to identify and trace illicit transactions with unprecedented accuracy. The cornerstone of this approach lies in the utilization of graph neural networks (GNNs), a cutting-edge technology capable of processing data represented as graphs. GNNs have proven their mettle in various domains, including drug discovery, computer vision, and natural language processing.

Elliptic 的创新方法利用深度学习模型、最先进的人工智能技术和海量数据集，以前所未有的准确性识别和追踪非法交易。这种方法的基石在于图神经网络（GNN）的利用，这是一种能够处理以图表示的数据的尖端技术。 GNN 已经在各个领域证明了自己的能力，包括药物发现、计算机视觉和自然语言处理。

Understanding the Significance: Money Laundering in the Crypto Age

理解意义：加密时代的洗钱

The rise of cryptocurrency has been accompanied by concerns about its potential to facilitate money laundering, a major enabler of ransomware and other cybercrimes. Cryptocurrency's anonymity, ease of cross-border movement, and ability to be concealed through crypto mixers have made it a haven for nefarious actors.

加密货币的兴起伴随着人们对其可能促进洗钱活动的担忧，洗钱活动是勒索软件和其他网络犯罪的主要推动者。加密货币的匿名性、跨境流动的便捷性以及通过加密货币混合器隐藏的能力使其成为不法分子的避风港。

The Role of Subgraphs in Unmasking Illicit Activity

子图在揭露非法活动中的作用

In collaboration with the MIT-IBM Watson AI Lab, Elliptic researchers have focused on subgraph representations, a technique for analyzing local structures within complex networks. They ingeniously applied this technique to the Bitcoin blockchain, enabling the identification of "subgraphs"–chains of transactions that represent laundered Bitcoin. By shifting the focus from illicit wallets to subgraphs, this approach provides a comprehensive view of the multi-hop laundering process.

Elliptic 研究人员与 MIT-IBM Watson AI 实验室合作，重点研究子图表示，这是一种分析复杂网络中局部结构的技术。他们巧妙地将这种技术应用于比特币区块链，从而能够识别“子图”——代表已洗钱比特币的交易链。通过将重点从非法钱包转移到子图，这种方法提供了多跳洗钱过程的全面视图。

Harnessing the Transparency of Blockchain Transactions

利用区块链交易的透明度

While cryptocurrency allows for anonymity, blockchains inherently expose the details of transactions and the participating entities. This transparency, in stark contrast to traditional financial systems, offers a significant advantage for law enforcement and financial institutions seeking to combat financial crime.

虽然加密货币允许匿名，但区块链本质上公开了交易和参与实体的详细信息。这种透明度与传统金融体系形成鲜明对比，为寻求打击金融犯罪的执法部门和金融机构提供了显着优势。

Creating a Massive Dataset for Enhanced Detection

创建海量数据集以增强检测

To facilitate the development of effective detection techniques, Elliptic meticulously crafted a colossal dataset of nearly 200 million transactions, dubbed Elliptic2. This dataset encompassed 122,000 labeled subgraphs of Bitcoin clusters, providing a rich source of information for machine learning models.

为了促进有效检测技术的开发，Elliptic 精心制作了一个包含近 2 亿笔交易的庞大数据集，称为 Elliptic2。该数据集包含 122,000 个比特币集群的标记子图，为机器学习模型提供了丰富的信息源。

Testing the Technique and Uncovering Novel Patterns

测试技术并发现新模式

Elliptic's collaboration with a crypto exchange served as a rigorous testing ground for the new technique. The model successfully identified 52 subgroups engaged in money laundering activities, a significant portion of which had eluded the exchange's traditional detection methods. This demonstrates the technique's ability to uncover hidden patterns and identify money laundering that would otherwise remain undetected.

Elliptic 与加密货币交易所的合作为新技术提供了严格的测试平台。该模型成功识别出 52 个从事洗钱活动的小组，其中很大一部分躲过了交易所的传统检测方法。这证明了该技术能够发现隐藏的模式并识别原本无法被发现的洗钱行为。

Identifying Novel Laundering Patterns and Previously Unknown Illicit Wallets

识别新的洗钱模式和以前未知的非法钱包

The AI model's keen detection capabilities extended to sophisticated laundering patterns, such as "peeling chains" and the use of "nested services." Peeling chains involve splitting digital assets into smaller amounts and sending them to different addresses. Nested services, on the other hand, facilitate the movement of funds through accounts at larger cryptocurrency exchanges, often without the exchange's knowledge or consent. Additionally, the model's ability to detect previously unknown illicit crypto wallets based on laundering patterns offers invaluable assistance to law enforcement, regulators, and blockchain analytics firms.

人工智能模型敏锐的检测能力扩展到复杂的洗钱模式，例如“剥皮链”和“嵌套服务”的使用。剥离链涉及将数字资产分割成更小的数量并将它们发送到不同的地址。另一方面，嵌套服务有助于通过大型加密货币交易所的账户进行资金流动，而交易所通常不知情或不同意。此外，该模型能够根据洗钱模式检测以前未知的非法加密钱包，为执法机构、监管机构和区块链分析公司提供了宝贵的帮助。

Publicly Available Dataset for Collaborative Progress

用于协作进步的公开数据集

In a spirit of collaboration, Elliptic has made its dataset publicly available to empower other researchers and organizations to develop novel techniques for detecting illicit cryptocurrency transactions. This gesture underscores Elliptic's commitment to fostering a safer and more transparent crypto ecosystem.

本着合作的精神，Elliptic 公开了其数据集，以使其他研究人员和组织能够开发检测非法加密货币交易的新技术。这一举措强调了 Elliptic 对培育更安全、更透明的加密生态系统的承诺。

The Growing Threat of Ransomware and the Need for Robust Detection

勒索软件的威胁日益增长以及稳健检测的需求

The escalating threat posed by ransomware and other financially motivated cybercrimes necessitates robust detection and prevention measures. Elliptic's breakthrough technology provides a powerful tool in the fight against these malicious activities.

勒索软件和其他出于经济动机的网络犯罪造成的威胁不断升级，因此需要采取强有力的检测和预防措施。 Elliptic 的突破性技术为打击这些恶意活动提供了强大的工具。

Success Stories in Tracking Stolen Digital Assets

追踪被盗数字资产的成功案例

Law enforcement agencies, including the FBI, have demonstrated remarkable success in tracking stolen digital assets on the blockchain. In one notable case, the FBI successfully recovered crypto stolen by North Korean-linked threat groups. The agency has also taken decisive action against crypto mixers, disrupting their operations and hindering the laundering of illicit funds.

包括联邦调查局在内的执法机构在追踪区块链上被盗的数字资产方面取得了显着的成功。在一个值得注意的案例中，联邦调查局成功追回了与朝鲜有关的威胁组织窃取的加密货币。该机构还对加密货币混合商采取了果断行动，扰乱了他们的运营并阻止了非法资金的洗钱活动。

Conclusion: A Transformative Step in Combating Financial Crime

结论：打击金融犯罪的变革性一步

Elliptic's AI-driven approach to money laundering detection on the Bitcoin blockchain represents a transformative leap forward in the fight against financial crime. Its ability to identify complex laundering patterns, uncover hidden relationships, and detect previously unknown illicit wallets empowers law enforcement and financial institutions with unprecedented capabilities. As the crypto landscape continues to evolve, Elliptic's technology will undoubtedly remain at the forefront, safeguarding the integrity of financial systems and protecting society from the insidious threats posed by money laundering and other illicit activities.

Elliptic 在比特币区块链上采用人工智能驱动的洗钱检测方法代表了打击金融犯罪的革命性飞跃。它能够识别复杂的洗钱模式、发现隐藏的关系以及检测以前未知的非法钱包，从而使执法机构和金融机构拥有前所未有的能力。随着加密领域的不断发展，Elliptic 的技术无疑将保持在最前沿，维护金融系统的完整性并保护社会免受洗钱和其他非法活动造成的潜在威胁。