Students look to improve bitcoin transparency

Students are examining ways to make Bitcoin more appealing to a wider range of businesses (Image: Shutterstock)

The intersection between transparency and privacy can be tricky. Crypto currency bitcoin is a good example of this as its purported anonymity can present problems in transactions and potentially lead to various kinds of fraud. In an effort to make the digital currency more attractive to a wider range of legitimate businesses, students at Trinity College Dublin are looking for ways to increase transparency in transactions without ditching the anonymity altogether and believe a "credit-check" database could be one answer.

Bitcoin is being used by more large and legitimate businesses. Microsoft last year announced it would accept bitcoin payments, and Bill Gates is a known fan, though the service remains US-only at this point.

The Trinity team says that bitcoin’s anti-fiat nature and lack of government regulation are what makes it attractive to many users, but some form of regulation might help, "if only to reduce the risk of fraudulent business practices or money laundering taking place behind Bitcoin’s closed doors."

The students' investigations focused on three questions: How much currency is in circulation, how is it being distributed (might someone currently be stockpiling?) and are there any concerning patterns in transactions?

Aren't such concerns already dealt with by the currency itself? Sort of. Though bitcoin is reasonably anonymous in that your name does not appear beside any particularly daft purchases, a record of every transaction made stays within the Blockchain. Almost like an immortal digital ledger, all transactions from the mining of each "coin" to every transfer made between "wallets" (where one stores their bitcoins) is recorded within it.

As the Bitcoin FAQ says: "All Bitcoin transactions are stored publicly and permanently on the network, which means anyone can see the balance and transactions of any Bitcoin address. However, the identity of the user behind an address remains unknown until information is revealed during a purchase or in other circumstances."

Cian Burns, a Masters student at Trinity, employed various helper websites and used his own laptop to auto-trawl through the enormous Blockchain to build a database of all the accounts held before attempting to link them together in a bid to understand the connections between some of them.

Given the anonymity of the system, it is hard to know how many accounts might be owned by one person or entity. However, once someone makes their bitcoin address public – in an email asking for payment, for example – a picture of their activity over time can be ascertained by looking at all the related addresses.

"The big benefit of such a picture is that if an address is involved in fraudulent activity, tracing related addresses could protect other users from further fraud," said Burns. "Our trawl gave us a unique insight into some very high-profile Bitcoin fraud cases that were being conducted across the world. Regulation is further down the line, but a database of accounts could certainly protect people and raise the appeal of Bitcoin for legitimate businesses."

One problem with bitcoin transfers is that they cannot be reversed, only refunded by the person or business receiving the payment. Given this, the students' idea of a running a sort of "credit check" before sending what could be an irreversible payment to a fraudulent body might be a good one. However, one thing the students haven't noted is that Bitcoin itself recommends that for anonymity all addresses should "only be used once." Building a database of dormant single use addresses might not be an effective way to run credit checks.

Linking Bitcoin users to geographic locations so as to keep a watch for suspicious inter-country bitcoin transactions is another potential area of study that the students will consider as they continue the project this year under the tutelage of Professor of Computer Science, Donal O'Mahony from Trinity’s School of Computer Science & Statistics.

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