A Bayesian Approach to Identify Bitcoin Users

Bitcoin is a digital currency and electronic payment system operating over a peer-to-peer network on the Internet. One of its most important properties is the high level of anonymity it provides for its users. The users are identified by their Bitcoin addresses, which are random strings in the public records of transactions, the blockchain. When a user initiates a Bitcoin-transaction, his Bitcoin client program relays messages to other clients through the Bitcoin network. Monitoring the propagation of these messages and analyzing them carefully reveal hidden relations. In this paper, we develop a mathematical model using a probabilistic approach to link Bitcoin addresses and transactions to the originator IP address. To utilize our model, we carried out experiments by installing more than a hundred modified Bitcoin clients distributed in the network to observe as many messages as possible. During a two month observation period we were able to identify several thousand Bitcoin clients and bind their transactions to geographical locations

Data mining for detecting Bitcoin Ponzi schemes

Soon after its introduction in 2009, Bitcoin has been adopted by cyber-criminals, which rely on its pseudonymity to implement virtually untraceable scams. One of the typical scams that operate on Bitcoin are the so-called Ponzi schemes. These are fraudulent investments which repay users with the funds invested by new users that join the scheme, and implode when it is no longer possible to find new investments. Despite being illegal in many countries, Ponzi schemes are now proliferating on Bitcoin, and they keep alluring new victims, who are plundered of millions of dollars. We apply data mining techniques to detect Bitcoin addresses related to Ponzi schemes. Our starting point is a dataset of features of real-world Ponzi schemes, that we construct by analysing, on the Bitcoin blockchain, the transactions used to perform the scams. We use this dataset to experiment with various machine learning algorithms, and we assess their effectiveness through standard validation protocols and performance metrics. The best of the classifiers we have experimented can identify most of the Ponzi schemes in the dataset, with a low number of false positives

Liquidity of bitcoin – insights from Polish and global markets

Bitcoin can be exchanged for other cryptocurrencies as well as for fiat currencies on many different platforms. Nevertheless, its real convertibility may be limited by market liquidity. The main aim of this article is to characterize and compare big and small bitcoin markets in terms of liquidity. I examine four platforms with high trade volume: Kraken, Bitstamp, BitFlyer and BTCBOX, as well as small entities which enable bitcoin to be traded in Polish zloty: BitBay and BitMarket. I compare the number of trades and the time between trades on selected bitcoin markets, determine the volume distribution throughout the day and analyse the dynamics of Amihud’s illiquidity measure – ILLIQ. I find that an exchange which is among the global leaders in terms of trading bitcoin in a particular traditional currency can be considered a smaller market in terms of trade volume in another traditional currency. Moreover, the results imply that BitBay and BitMarket can be perceived as local markets. They are mainly used for trading in Polish zloty, and are illiquid in terms of trading in the remaining traditional currencies. Home bias, the fact that they offer a possibility of trading in a less popular currency (in comparison to the world reserve currencies), and that have their interface in Polish, may give these platforms a competitive advantage.Bitcoinem można obracać na wielu różnych platformach, wykorzystując do tego inne kryptowaluty, jak również waluty tradycyjne. Niemniej jego rzeczywista wymienialność może być ograniczona przez płynność rynku. Głównym celem artykułu jest scharakteryzowanie i porównanie wybranych giełd kryptowalut pod względem płynności. W tym celu przeanalizowano cztery platformy, które odznaczają się wysokim wolumenem obrotu: Kraken, Bitstamp, BitFlyer i BTCBOX, a także dwa małe podmioty umożliwiające handel w polskim złotym: BitBay i BitMarket. W artykule przedstawiono porównanie rynków pod względem liczby zawartych transakcji, średniego czasu pomiędzy kolejnymi transakcjami czy rozkładu wolumenu obrotu w ciągu dnia. Ponadto przeanalizowano zmiany w czasie miary płynności – ILLIQ. Wyniki pozwoliły stwierdzić, że platforma, która znajduje się wśród globalnych liderów w obrocie bitcoinem w danej walucie tradycyjnej, może być postrzegana jako podmiot mały, jeśli zostanie wzięty pod uwagę obrót w innej walucie tradycyjnej. Ponadto najbardziej popularne platformy umożliwiające wymianę bitcoina na polskiego złotego, czyli BitBay i BitMarket, mogą być uznane za rynki lokalne. Są one głównie wykorzystywane do handlu w złotym. W przypadku obrotu bitcoinem w innych walutach tradycyjnych cechuje je bardzo niska płynność. Czynniki takie jak home bias, możliwość handlu bitcoinem w mniej popularnej walucie tradycyjnej (w porównaniu ze światowymi walutami rezerwowymi) oraz interfejs użytkownika w języku polskim mogą dawać pewną przewagę konkurencyjną tym platformom