Related papers: Benchmarking GNNs Using Lightning Network Data
With emergence of blockchain technologies and the associated cryptocurrencies, such as Bitcoin, understanding network dynamics behind Blockchain graphs has become a rapidly evolving research direction. Unlike other financial networks, such…
This paper reviews the applications of Graph Neural Networks (GNNs), Graph Convolutional Networks (GCNs), and Convolutional Neural Networks (CNNs) in blockchain technology. As the complexity and adoption of blockchain networks continue to…
Bitcoin is a cryptocurrency that features a distributed, decentralized and trustworthy mechanism, which has made Bitcoin a popular global transaction platform. The transaction efficiency among nations and the privacy benefiting from address…
The Bitcoin Lightning Network (BLN) was launched in 2018 to scale up the number of transactions between Bitcoin owners. Although several contributions concerning the analysis of the BLN binary structure have recently appeared in the…
Bitcoin transactions include unspent transaction outputs (UTXOs) as their inputs and generate one or more newly owned UTXOs at specified addresses. Each UTXO can only be used as an input in a transaction once, and using it in two or more…
The rise of cryptocurrencies like Bitcoin, which enable transactions with a degree of pseudonymity, has led to a surge in various illicit activities, including ransomware payments and transactions on darknet markets. These illegal…
To improve transaction rates, many cryptocurrencies have implemented so-called ''Layer-2'' transaction protocols, where payments are routed across networks of private payment channels. However, for a given transaction, not every network…
Bitcoin has emerged as a revolutionary payment system with its decentralized ledger concept; however it has significant problems such as high transaction fees and low throughput. Lightning Network (LN), which was introduced much later,…
While transactions with cryptocurrencies such as Ethereum are becoming more prevalent, fraud and other criminal transactions are not uncommon. Graph analysis algorithms and machine learning techniques detect suspicious transactions that…
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…
Payment channel networks (PCNs) are a promising solution to the scalability problem of cryptocurrencies. Any two users connected by a payment channel in the network can theoretically send an unbounded number of instant, costless…
Bitcoin is a cryptocurrency attracting a lot of interest both from the general public and researchers. There is an ongoing debate on the question of users' anonymity: while the Bitcoin protocol has been designed to ensure that the activity…
Bitcoin (BTC) pseudonyms (layer 1) can effectively be deanonymized using heuristic clustering techniques. However, while performing transactions off-chain (layer 2) in the Lightning Network (LN) seems to enhance privacy, a systematic…
Bitcoin is one of the decentralized cryptocurrencies powered by a peer-to-peer blockchain network. Parties who trade in the bitcoin network are not required to disclose any personal information. Such property of anonymity, however,…
Payment channel networks are a highly discussed approach for improving scalability of cryptocurrencies such as Bitcoin. As they allow processing transactions off-chain, payment channel networks are referred to as second layer technology,…
The fundamental building blocks of the Bitcoin lightning network are bidirectional payment channels. We describe an extension of payment channels in the Proofgold network which allow the two parties to bet on whether a proposition will be…
Cryptocurrency off-chain networks such as Lightning (e.g., Bitcoin) or Raiden (e.g., Ethereum) aim to increase the scalability of traditional on-chain transactions. To support nodes in learning about possible paths to route their…
Lightning Network (LN) addresses the scalability problem of Bitcoin by leveraging off-chain transactions. Nevertheless, it is not possible to run LN on resource-constrained IoT devices due to its storage, memory, and processing…
Graph Neural Networks (GNNs) have emerged as a promising tool to handle data exhibiting an irregular structure. However, most GNN architectures perform well on homophilic datasets, where the labels of neighboring nodes are likely to be the…
Real data collected from different applications that have additional topological structures and connection information are amenable to be represented as a weighted graph. Considering the node labeling problem, Graph Neural Networks (GNNs)…