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The biharmonic distance is a fundamental metric on graphs that measures the dissimilarity between two nodes, capturing both local and global structures. It has found applications across various fields, including network centrality, graph…
Privacy protection mechanisms are a fundamental aspect of security in cryptocurrency systems, particularly in decentralized networks such as Bitcoin. Although Bitcoin addresses are not directly associated with real-world identities, this…
Over the last two decades, network theory has shown to be a fruitful paradigm in understanding the organization and functioning of real-world complex systems. One technique helpful to this endeavor is identifying functionally influential…
Money laundering presents a persistent challenge for financial institutions worldwide, while criminal organizations constantly evolve their tactics to bypass detection systems. Traditional anti-money laundering approaches mainly rely on…
Mining pools, the main components of the Bitcoin network, dominate the computing resources and play essential roles in network security and performance aspects. Although many existing measurements of the Bitcoin network are available,…
The Lightning Network, a payment channel network with a market cap of over 192M USD, is designed to resolve Bitcoin's scalability issues through fast off-chain transactions. There are multiple Lightning Network client implementations, all…
The detection of outliers within cryptocurrency limit order books (LOBs) is of paramount importance for comprehending market dynamics, particularly in highly volatile and nascent regulatory environments. This study conducts a comprehensive…
Money laundering is a critical step in the cyber crime process which is experiencing some changes as hackers and their criminal colleagues continually alter and optimize payment mechanisms. Conducting quantitative research on underground…
Blockchain has been considered as an important technique to enable secure management of virtual network functions and network slices. To understand such capabilities of a blockchain, e.g. transaction confirmation time, demands a thorough…
Random Walk is a basic algorithm to explore the structure of networks, which can be used in many tasks, such as local community detection and network embedding. Existing random walk methods are based on single networks that contain limited…
Automatic feature learning algorithms are at the forefront of modern day machine learning research. We present a novel algorithm, supervised Q-walk, which applies Q-learning to generate random walks on graphs such that the walks prove to be…
Due to their rapid growth and deployment, the Internet of things (IoT) have become a central aspect of our daily lives. Unfortunately, IoT devices tend to have many vulnerabilities which can be exploited by an attacker. Unsupervised…
Ethereum is currently the second largest blockchain by market capitalization and a popular platform for cryptocurrencies. As it has grown, the high value present and the anonymity afforded by the technology have led Ethereum to become a…
In the Internet of Things (IoT) domain, devices need a platform to transact seamlessly without a trusted intermediary. Although Distributed Ledger Technologies (DLTs) could provide such a platform, blockchains, such as Bitcoin, were not…
This work proposes a novel proof-of-work blockchain incentive scheme such that, barring exogenous motivations, following the protocol is guaranteed to be the optimal strategy for miners. Our blockchain takes the form of a directed acyclic…
Blockchains are significantly easing trade finance, with billions of dollars worth of assets being transacted daily. However, analyzing these networks remains challenging due to the sheer volume and complexity of the data. We introduce a…
Cryptocurrencies have emerged as a new form of digital money that has not escaped the eyes of cyber-attackers. Traditionally, they have been maliciously used as a medium of exchange for proceeds of crime in the cyber dark-market by…
For preserving privacy, blockchains can be equipped with dedicated mechanisms to anonymize participants. However, these mechanism often take only the abstraction layer of blockchains into account whereas observations of the underlying…
Insider trading is one of the numerous white collar crimes that can contribute to the instability of the economy. Traditionally, the detection of illegal insider trades has been a human-driven process. In this paper, we collect the insider…
This study investigates fraud detection in ride hailing platforms through Graph Neural Networks (GNNs),focusing on the effectiveness of various models. By analyzing prevalent fraudulent activities, the research highlights and compares the…