This dataset was created for research on blockchain anomaly and fraud detection. And donated to IEEE data port online community.

https://github.com/epicprojects/blockchain-anomaly-detection

 

Files: 

bitcoin_hacks_2010_2013.csv: Contains known hashes of bitcoin theft/malicious transactions from 2010-2013

malicious_tx_in.csv: Contains hashes of input transactions flowing into malicious transactions.

Instructions: 

The dataset contains transaction hashes of all bitcoin Heists, Thefts, Hacks, Scams, and Losses from 2010-2014. These datasets are constructed from the information bitcoin forum (https://bitcointalk.org/index.php?topic=576337.0) and Blockchain.com

 References:

  1. https://arxiv.org/abs/1611.03942

  2. https://arxiv.org/abs/1611.03941

Categories:
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Information:

 This dataset was created for research on blockchain anomaly and fraud detection. And donated to IEEE data port online community.

Research experiments for this dataset can be found at https://github.com/epicprojects/blockchain-anomaly-detection

 

 

Instructions: 

 

*This dataset is created by parsing raw bitcoin .BLK files. Using this dataset one can create a directed acyclic graph (DAG) of bitcoin transaction network as mentioned in references.

 

DIMENSIONS:

  • tx_hash_from: Input transaction hash
  • tx_hash_to: Output transaction hash
  • datetime: Represents the date and time of the transaction
  • amount_bitcoins: The amount of bitcoins transferred.

 

 

REFERENCES:

  1. https://arxiv.org/abs/1611.03942
  2. https://arxiv.org/abs/1611.03941
  3. https://arxiv.org/abs/1107.4524
  4. http://anonymity-in-bitcoin.blogspot.com/2011/09/code-datasets-and-spsn1...
  5. http://snap.stanford.edu/class/cs224w-2013/projects2013/cs224w-030-final...

 

 

Categories:
2141 Views

Information:

This dataset was created for research on blockchain anomaly and fraud detection. And donated to IEEE data port online community. 

https://github.com/epicprojects/blockchain-anomaly-detection

 

 

 

Instructions: 

A directed-acyclic graph is created from the bitcoin transaction data and metadata is extracted to create this dataset. 

 

DIMENSIONS:

  • tx_hash: Hash of the bitcoin transaction.
  • indegree: Number of transactions that are inputs of tx_hash
  • outdegree: Number of transactions that are outputs of tx_hash.
  • in_btc: Number of bitcoins on each incoming edge to tx_hash.
  • out_btc: Number of bitcoins on each outgoing edge from tx_hash.
  • total_btc: Net number of bitcoins flowing in and out from tx_hash.
  • mean_in_btc: Average number of bitcoins flowing in for tx_hash.
  • mean_out_btc: Average number of bitcoins flowing out for tx_hash.
  • in-malicious: Will be 1 if the tx_hash is an input of a malicious transaction.
  • out-malicious: Will be 1 if the tx_hash is an output of a malicious transaction.
  • is-malicious: Will be 1 if the tx_hash is a malicious transaction.
  • out_and_tx_malicious: Will be 1 if the tx_hash is a malicious transaction or an output of a malicious transaction.
  • all_malicious: Will be 1 if the tx_hash is a malicious transaction or an output of a malicious transaction or input of a malicious transaction.

 

REFERENCES:

  1. https://arxiv.org/abs/1611.03942
  2. https://arxiv.org/abs/1611.03941
  3. https://arxiv.org/abs/1107.4524
  4. http://anonymity-in-bitcoin.blogspot.com/2011/09/code-datasets-and-spsn1...
  5. http://snap.stanford.edu/class/cs224w-2013/projects2013/cs224w-030-final...

 

 

Categories:
1197 Views