Elliptic 的人工智慧突破破解了比特幣洗錢之謎

區塊鏈分析公司 Elliptic 開發了一種使用深度學習、人工智慧技術和大量資料集來識別和追蹤比特幣區塊鏈上洗錢活動的方法。這種方法的重點是檢測“子圖”，即代表已洗錢比特幣的交易鏈，使調查人員能夠比監控個人錢包更有效地分析非法活動。

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

破解比特幣區塊鏈洗錢之謎：Elliptic 的人工智慧突破

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.

資金透過複雜的金融網絡非法流動長期以來給執法機構、監管機構和金融分析師等帶來了巨大的挑戰。然而，區塊鏈分析公司 Elliptic 的突破性發展有望徹底改變比特幣區塊鏈上洗錢的偵測和追蹤。

Harnessing the Power of AI and Graph Neural Networks

利用人工智慧和圖神經網路的力量

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 的創新方法利用深度學習模型、最先進的人工智慧技術和大量資料集，以前所未有的準確性識別和追蹤非法交易。這種方法的基石在於圖神經網路（GNN）的利用，這是一種能夠處理以圖表示的資料的尖端技術。 GNN 已經在各個領域證明了自己的能力，包括藥物發現、電腦視覺和自然語言處理。

Understanding the Significance: Money Laundering in the Crypto Age

理解意義：加密時代的洗錢

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.

加密貨幣的興起伴隨著人們對其可能促進洗錢活動的擔憂，洗錢活動是勒索軟體和其他網路犯罪的主要推動者。加密貨幣的匿名性、跨境流動的便利性以及透過加密貨幣混合器隱藏的能力使其成為不法分子的避風港。

The Role of Subgraphs in Unmasking Illicit Activity

子圖在揭露非法活動中的作用

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 研究人員與 MIT-IBM Watson AI 實驗室合作，重點研究子圖表示，這是一種分析複雜網路中局部結構的技術。他們巧妙地將這種技術應用於比特幣區塊鏈，從而能夠識別「子圖」——代表已洗錢比特幣的交易鏈。透過將重點從非法錢包轉移到子圖，這種方法提供了多跳洗錢過程的全面視圖。

Harnessing the Transparency of Blockchain Transactions

利用區塊鏈交易的透明度

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.

雖然加密貨幣允許匿名，但區塊鏈本質上公開了交易和參與實體的詳細資訊。這種透明度與傳統金融體系形成鮮明對比，為尋求打擊金融犯罪的執法部門和金融機構提供了顯著優勢。

Creating a Massive Dataset for Enhanced Detection

建立海量資料集以增強檢測

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.

為了促進有效檢測技術的開發，Elliptic 精心製作了一個包含近 2 億筆交易的龐大資料集，稱為 Elliptic2。該資料集包含 122,000 個比特幣集群的標記子圖，為機器學習模型提供了豐富的資訊來源。

Testing the Technique and Uncovering Novel Patterns

測試技術並發現新模式

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 與加密貨幣交易所的合作為新技術提供了嚴格的測試平台。該模型成功識別出 52 個從事洗錢活動的小組，其中很大一部分躲過了交易所的傳統檢測方法。這證明了該技術能夠發現隱藏的模式並識別原本無法被發現的洗錢行為。

Identifying Novel Laundering Patterns and Previously Unknown Illicit Wallets

識別新的洗錢模式和以前未知的非法錢包

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.

人工智慧模式敏銳的檢測能力擴展到複雜的洗錢模式，例如「剝皮鏈」和「嵌套服務」的使用。剝離鏈涉及將數位資產分割成更小的數量並將它們發送到不同的地址。另一方面，嵌套服務有助於透過大型加密貨幣交易所的帳戶進行資金流動，而交易所通常不知情或不同意。此外，該模型能夠根據洗錢模式檢測以前未知的非法加密錢包，為執法機構、監管機構和區塊鏈分析公司提供了寶貴的幫助。

Publicly Available Dataset for Collaborative Progress

用於協作進步的公開資料集

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.

本著合作的精神，Elliptic 公開了其資料集，以使其他研究人員和組織能夠開發檢測非法加密貨幣交易的新技術。這項措施強調了 Elliptic 對培育更安全、更透明的加密生態系統的承諾。

The Growing Threat of Ransomware and the Need for Robust Detection

勒索軟體的威脅日益增長以及穩健檢測的需求

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.

勒索軟體和其他出於經濟動機的網路犯罪造成的威脅不斷升級，因此需要採取強有力的偵測和預防措施。 Elliptic 的突破性技術為打擊這些惡意活動提供了強大的工具。

Success Stories in Tracking Stolen Digital Assets

追蹤被盜數位資產的成功案例

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.

包括聯邦調查局在內的執法機構在追蹤區塊鏈上被盜的數位資產方面取得了顯著的成功。在一個值得注意的案例中，聯邦調查局成功追回了與北韓有關的威脅組織竊取的加密貨幣。該機構還對加密貨幣混合商採取了果斷行動，擾亂了他們的營運並阻止了非法資金的洗錢活動。

Conclusion: A Transformative Step in Combating Financial Crime

結論：打擊金融犯罪的變革性一步

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 在比特幣區塊鏈上採用人工智慧驅動的洗錢檢測方法代表了打擊金融犯罪的革命性飛躍。它能夠識別複雜的洗錢模式、發現隱藏的關係以及檢測以前未知的非法錢包，從而使執法機構和金融機構擁有前所未有的能力。隨著加密領域的不斷發展，Elliptic 的技術無疑將保持在最前沿，維護金融系統的完整性並保護社會免受洗錢和其他非法活動造成的潛在威脅。