Uncovering Strategies for Identifying Underground Bitcoin Transactions through Algorithmic Development
In a significant move for the cryptocurrency industry, Elliptic, MIT, and IBM have joined forces to release a dataset of 200,000 Bitcoin transactions. The dataset, collected since 2011, is not publicly available in a single accessible location but can be accessed through academic partnerships or direct collaboration with the involved organizations.
The dataset is designed to aid the development of machine learning algorithms and to detect illicit transactions. Each transaction in the dataset comes with 166 associated features, including the transaction fee and a time interval for when a transaction appeared on the blockchain. The transactions have been labeled as licit, illicit, and unknown.
It's important to note that the dataset is a collection of transactions with various labels and associated features, but it does not come with an image from Pixabay. The image, which is freely available, is a visual aid for researchers working with the dataset and is intended to be used in conjunction with it. However, the image does not provide any additional transaction data or affect the 166 associated features for each transaction.
The image from Pixabay is not a product of Elliptic, MIT, or IBM, and its use is not a requirement for using the dataset for research purposes. The full dataset, along with the accompanying image, has been released for research purposes to foster the development of machine learning algorithms and improve the understanding of Bitcoin transactions.
While the dataset offers a wealth of information for researchers, it's crucial to approach the data with caution and maintain the integrity of the research. The dataset, like any other, should be used responsibly and ethically to ensure the advancement of knowledge in the field without compromising the privacy or security of individuals or organizations involved in the transactions.
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