Bitcoin [BTC] thefts: Cambridge scholars find an ‘ancient’ way to combat future cryptocurrency crimes
While the true number of Bitcoins [BTC] stolen till date will actually remain a mystery, the official number exceeds $1 billion in BTCs. Transactions in the Bitcoin ecosystem are not anonymous and are public in nature, but they are quite untraceable. The reason as to why they are impossible to track is because, unlike each US Dollar bill, which is engraved with a serial number, individual Bitcoins are not numbered and hence, trailing the genesis of the coins [or stolen coins] is pretty elusive.
However, few Cambridge University scholars namely, Mansoor Ahmed, Ilia Shumailor and Rose Anderson, have released a paper called – Tendrils of crime- visualizing the diffusion of stolen coins, elucidating a system to trace back the stolen coins which can be further reclaimed by the victim it was stolen from.
The paper also said that ‘one-to-many’ kind of transactions are, although very rare [as many wallets do not permit the transactions from one source to multiple entities at a given time], the ones which are commonly used for money laundering purposes.
The paper, in brief, explains two types of tracking processes, of which the second one seems to be helpful in drawing a recourse of the stolen coin (or coins). This approach is called Taintchain, which uses a device called FIFO (stands for first in, first out). FIFO is an ancient accounting method that has been applied in various fields including law and most recently – in the cryptocurrency space.
It fundamentally splits each Bitcoin into its smallest unit called satoshis, i.e., 1 Bitcoin into 100 million unique satoshis carrying all the information of its movement. The FIFO algorithm enables trailing the course of the coin movement right back to the genesis wallet. The rule that applies here is that if the first coins that got into the wallet were stolen, then the first ones which were paid out of the wallet are considered to be stolen too.
With graphical interpretations along with apt visualization tools, the paper asserts the second approach to be much more practical. The paper concluded by bringing into notice that despite several shortcomings, this approach seems to work and that they are up for improvisation.
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