Related papers: Significant Digits: Using Large-Scale Blockchain D…
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.…
Blockchain technology has rapidly emerged to mainstream attention, while its publicly accessible, heterogeneous, massive-volume, and temporal data are reminiscent of the complex dynamics encountered during the last decade of big data.…
Graph Neural Networks (GNNs) have achieved promising results in tasks such as node classification and graph classification. However, recent studies reveal that GNNs are vulnerable to backdoor attacks, posing a significant threat to their…
The detection of frauds in credit card transactions is a major topic in financial research, of profound economic implications. While this has hitherto been tackled through data analysis techniques, the resemblances between this and other…
Blockchain is a growing decentralized system built for transparency and immutability. There have been several major attacks on blockchain-based systems, leaving a gap in the trustability of this system. This article presents a comprehensive…
Non-fungible tokens (NFTs) serve as a representative form of digital asset ownership and have attracted numerous investors, creators, and tech enthusiasts in recent years. However, related fraud activities, especially phishing scams, have…
Benford's Law describes the finding that the distribution of leading (or leftmost) digits of innumerable datasets follows a well-defined logarithmic trend, rather than an intuitive uniformity. In practice this means that the most common…
We investigate the relationship between underlying blockchain mechanism of cryptocurrencies and its distributional characteristics. In addition to price, we emphasise on using actual block size and block time as the operational features of…
The number of blockchain users has tremendously grown in recent years. As an unintended consequence, e-crime transactions on blockchains has been on the rise. Consequently, public blockchains have become a hotbed of research for developing…
Cryptocurrencies are no longer just the preferred option for cybercriminal activities on darknets, due to the increasing adoption in mainstream applications. This is partly due to the transparency associated with the underpinning ledgers,…
Subgraph representation learning is a technique for analyzing local structures (or shapes) within complex networks. Enabled by recent developments in scalable Graph Neural Networks (GNNs), this approach encodes relational information at a…
Blockchain networks are critical for safeguarding digital transactions and assets, but they are increasingly targeted by ransomware attacks exploiting zero-day vulnerabilities. Traditional detection techniques struggle due to the complexity…
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 uses blockchain technology to maintain transactions order and provides probabilistic guarantee to prevent double-spending, assuming that an attacker's computational power does not exceed %50 of the network power. In this paper, we…
Link Prediction is an important and well-studied problem for social networks. Given a snapshot of a graph, the link prediction problem predicts which new interactions between members are most likely to occur in the near future. As networks…
Light nodes in blockchain systems are known to be vulnerable to data availability (DA) attacks where they accept an invalid block with unavailable portions. Previous works have used LDPC and 2-D Reed Solomon (2D-RS) codes with Merkle Trees…
Blockchain has recently been depicted as a secure protocol for information exchange in cyber-physical microgrids. However, it is still found vulnerable to consensus manipulation attacks. These stealth attacks are often difficult to detect…
Blockchain technology is widely used in various fields due to its ability to provide decentralization and trustless security. This is a fundamental understanding held by many advocates, but it is misunderstood, leading participants to fail…
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…
The unique properties of blockchain enable central requirements of distributed secure logging: Immutability, integrity, and availability. Especially when providing transparency about data usages, a blockchain-based secure log can be…