Related papers: Demystifying Bitcoin Address Behavior via Graph Ne…
Cybercriminals often leverage Bitcoin for their illicit activities. In this work, we propose back-and-forth exploration, a novel automated Bitcoin transaction tracing technique to identify cybercrime financial relationships. Given seed…
The decentralization, redundancy, and pseudo-anonymity features have made permission-less public blockchain platforms attractive for adoption as technology platforms for cryptocurrencies. However, such adoption has enabled cybercriminals to…
Since its 2009 genesis block, the Bitcoin network has processed >1.08 billion (B) transactions representing >8.72B BTC, offering rich potential for machine learning (ML); yet, its pseudonymity and obscured flow of funds inherent in its…
Over 900 million Bitcoin transactions have been recorded, posing considerable challenges for machine learning in terms of computation time and maintaining prediction accuracy. We propose an innovative approach using quantum-inspired…
Blockchain is a distributed ledger, which is protected against malicious modifications by means of cryptographic tools, e.g. digital signatures and hash functions. One of the most prominent applications of blockchains is cryptocurrencies,…
Blockchain technology and, in particular, blockchain-based transaction offers us information that has never been seen before in the financial world. In contrast to fiat currencies, transactions through virtual currencies like Bitcoin are…
Bitcoin is a peer-to-peer electronic payment system that has rapidly grown in popularity in recent years. Usually, the complete history of Bitcoin blockchain data must be queried to acquire variables with economic meaning. This task has…
In a ring-signature-based anonymous cryptocurrency, signers of a transaction are hidden among a set of potential signers, called a ring, whose size is much smaller than the number of all users. The ring-membership relations specified by the…
Detecting illicit nodes on blockchain networks is a valuable task for strengthening future regulation. Recent machine learning-based methods proposed to tackle the tasks are using some blockchain transaction datasets with a small portion of…
Bitcoin has been subject to illicit activities more often than probably any other financial assets, due to the pseudo-anonymous nature of its transacting entities. An ideal detection model is expected to achieve all the three properties of…
This work is organized as follows. In the first section we review the prior work and we have obtained our data. Next, we will look at address reuse in the Bitcoin network. We show that a great portion of users reuse their addresses which…
In recent years blockchain technology has received tremendous attention. Blockchain users are known by a changeable Public Key (PK) that introduces a level of anonymity, however, studies have shown that anonymized transactions can be linked…
The temporal nature of modeling accounts as nodes and transactions as directed edges in a directed graph -- for a blockchain, enables us to understand the behavior (malicious or benign) of the accounts. Predictive classification of accounts…
As the use of Blockchain for digital payments continues to rise in popularity, it also becomes susceptible to various malicious attacks. Successfully detecting anomalies within Blockchain transactions is essential for bolstering trust in…
Graph neural networks (GNNs) offer a principled approach to financial fraud detection by jointly learning from node features and transaction graph topology. However, their effectiveness on real-world anti-money laundering (AML) benchmarks…
Different types of malicious activities have been flagged in multiple permissionless blockchains such as bitcoin, Ethereum etc. While some malicious activities exploit vulnerabilities in the infrastructure of the blockchain, some target its…
The purpose of this work was to perform a network analysis on the rapidly growing bitcoin transaction network. Using a web-socket API, we collected data on all transactions occurring during a six hour window. Sender and receiver addresses…
Graph embeddings have been proposed to map graph data to low dimensional space for downstream processing (e.g., node classification or link prediction). With the increasing collection of personal data, graph embeddings can be trained on…
Blockchains are typically managed by peer-to-peer (P2P) networks providing the support and substrate to the so-called distributed ledger (DLT), a replicated, shared, and synchronized data structure, geographically spread across multiple…
With the rapid increase of threats on the Internet, people are continuously seeking privacy and anonymity. Services such as Bitcoin and Tor were introduced to provide anonymity for online transactions and Web browsing. Due to its…