Primerjava metod sledenja označenih kovancev v omrežju Bitcoin

Kokelj, Žiga (avtor), Šubelj, Lovro (mentor), Trampuš, Matej (komentor)

Bitcoin s svojo odprtostjo in psevdonimnostjo nudi mnoge priložnosti in izzive. Eden od izzivov je sledenje označenim kovancem skozi omrežje Bit- coin transakcij z namenom opozarjanja na izhode transakcij, ki izvirajo iz kriminalnih dejanj. Zaradi velikega števila vozlišč in kompleksnosti grafa transakcij smo razvili metode za preiskovanje tega omrežja. V magistrski nalogi smo implementirali znane metode in jim dodali novo metodo, ime- novano COMB. Pripravili in optimizirali smo podatkovno bazo, ki omogoča tako preiskovanje ter pridobili vzorca sumljivih in naključnih transakcij. Na njih smo pognali metode in analizirali dobljene rezultate. Ugotovili smo, da imajo vse metode določene prednosti in slabosti. Analizirali smo preseke grafov, nastalih z različnimi metodami, saj imajo te transakcije višjo ver- jetnost za povezavo z izvorno transakcijo. Pripravili smo tudi podatkovno bazo, ki vključuje dodatne podatke, ki jih metode pri svojem odločanju lahko uporabijo. Analiza je pokazala velik potencial tega pristopa, saj smo že na razmeroma majhni bazi v več primerih prišli do znanih transakcij.

• Jezik: Slovenski jezik
• Ključne besede: Bitcoin, veriženje blokov, analiza omrežij
• Vrsta gradiva: Magistrsko delo/naloga
• Tipologija: 2.09 - Magistrsko delo
• Organizacija: FRI - Fakulteta za računalništvo in informatiko
• Leto izida: 2021
• PID: 20.500.12556/RUL-133698
• COBISS.SI-ID: 89826563
• Datum objave v RUL: 10.12.2021

KOKELJ, Žiga, 2021, Primerjava metod sledenja označenih kovancev v omrežju Bitcoin [na spletu]. Magistrsko delo. [Dostopano 11 april 2025]. Pridobljeno s: https://repozitorij.uni-lj.si/IzpisGradiva.php?lang=slv&id=133698

Sekundarni jezik

• Jezik: Angleški jezik
• Naslov: Comparison of tainting analysis methods in Bitcoin network

Izvleček

Bitcoin offers many new opportunities and challenges with its pseudonymity and open source nature. One of the challenges is performing taint analysis in order to follow coins that originated from criminal activities. Due to a large number of nodes and the complexity of the Bitcoin transaction graph, methods for the performance of taint analysis have been developed. In this master’s thesis, existing methods were implemented and furthermore a new method called COMB was proposed. A database that supports running these methods was put together. For the testing purpose, two data sets of starting transaction outputs were prepared. After executing all methods on the data sets and analysis of the results, it was concluded that all methods have pros and cons. The intersections of graphs produced by different algorithms from the same starting inputs were analyzed, because they contain transactions with a higher probability of being connected to the starting transaction out- put. Another database with off-chain data that can be used in implemented methods was developed. Even with a relatively small database, we were able to reach some known transactions with implemented methods, showing the big potential of this technique.

• Ključne besede: Bitcoin, blockchain, network analysis