In the world of digital currency trading, Bitcoin has always been the focus of much attention. Recently, the AI Lab at MIT conducted a remarkable study that analyzed up to 200,000 Bitcoin transactions. Surprisingly, they revealed a startling fact: only 2% of the transactions were illegal. This study not only brings us a new understanding of digital currency trading, but also provides valuable information for regulators and investors. Let's take a deeper look at this major discovery.

Bitcoin, a virtual currency, has been controversial since its inception. Its decentralized nature makes it a choice for many illegal transactions, but the MIT study brings a new perspective to this view. Through an in-depth analysis of large-scale Bitcoin transaction data, the research team found that only 2% of Bitcoin transactions involved illegal activities. This low number exceeded many people's expectations and also hinted at the potential of Bitcoin as a legal digital currency.

The use of AI technology adds a layer of cutting-edge scientific and technological aura to this study. Through artificial intelligence data mining and analysis, researchers are able to dig deep into the huge Bitcoin transaction data and discover hidden patterns and characteristics. This research method, which combines human wisdom and machine computing power, not only improves the efficiency of data analysis, but also reveals to us the more complex reality behind digital currency transactions.

It is worth mentioning that this study has important implications for regulators and government departments. As digital currencies such as Bitcoin continue to grow and develop, regulatory issues have become increasingly prominent. However, MIT's research results show that most Bitcoin transactions are legal, which means that regulators need to more accurately locate illegal activities rather than simply viewing digital currencies as risks.

In the eyes of investors, the digital currency market has always been a field where risks and opportunities coexist. MIT's research may provide investors with more confidence and basis. Knowing that only a very small number of Bitcoin transactions have illegal problems, investors can participate in the digital currency market with more confidence, but they also need to remain vigilant to avoid potential risks.

In general, the study of 200,000 Bitcoin transactions conducted by the MIT AI Lab revealed a surprising fact: only 2% of the transactions were illegal. This finding not only brings new insights to the digital currency market, but also provides valuable references for regulators, investors and academia. The future of digital currency is full of opportunities and challenges, and only through unremitting exploration and research can we better grasp the development direction of this emerging field.

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According to Coindesk on August 2, blockchain analysis company Elliptic has partnered with the Massachusetts Institute of Technology (MIT) to release a public dataset of Bitcoin transactions associated with illegal activities.

(Source: Pixabay)

The team's research details how researchers at the MIT-IBM Watson AI Lab used machine learning software to classify 203,769 Bitcoin node transactions with a total value of approximately $6 billion. The study explored whether artificial intelligence can help current anti-money laundering processes.

After checking the association of these nodes with known entities, the researchers found that only 2% of the 200,000 Bitcoin transactions were considered illegal, another 21% were confirmed as legal, but the vast majority of transactions (about 77%) remained unclassified. It is reported that so far, there have been an estimated 440 million Bitcoin transactions since its launch in 2009.

It should be clear that this 2% of illegal transactions came from the previously undisclosed Elliptic
dataset and was only found by MIT researchers through analysis. However, the data is similar to a study by another analytics firm, Chainalysis, which estimated that only 1% of Bitcoin transactions in 2019 were related to illegal activity.

Since law enforcement agencies around the world often hire Elliptic to identify illegal activities involving cryptocurrencies, this study aims to find ways to help distinguish illegal from legal use of Bitcoin, especially for individuals without bank accounts or other unknown entities.

Tom Robinson, co-founder of Elliptic, said:

In general, the key problem with compliance is false positives (negatives are judged as positive). An important part of this study is to reduce the number of false positives. A key finding is that machine learning technology can play a very effective role in discovering illegal transactions.

Robinson added that sometimes, based on pre-stored data from dark web markets, ransomware attacks and other criminal investigations, the software is able to find patterns that are difficult to describe but match known entities.

After completing the academic research, Elliptic made the dataset public to encourage open source.

Mark Weber, a researcher at MIT, said:

We are sharing our early experiments in anti-money laundering with domain experts to solicit feedback. At the same time, we also hope that the release of the Elliptic dataset will inspire others to join in and jointly develop new AML technologies and models to improve the security of the financial system.

In April, CNBC reported that increased global criminal activity may drive a surge in demand for $100 bills. A 2017 report by the American Institute for Economic Research estimated that more than a third of all U.S. currency in circulation is used by criminals and tax fraudsters.