Adaptive attention-based graph representation learning to detect phishing accounts on the ethereum blockchain

H Sun, Z Liu, S Wang, H Wang - IEEE Transactions on Network …, 2024‏ - ieeexplore.ieee.org
With Ethereum blockchain advancement, the Ethereum platform gathers numerous users. In
this context, traditional phishing appears new fraud methods, resulting in significant losses …

[HTML][HTML] Blockchain-based data breach detection: approaches, challenges, and future directions

K Ansar, M Ahmed, M Helfert, J Kim - Mathematics, 2023‏ - mdpi.com
In cybersecurity, personal data breaches have become one of the significant issues. This
fact indicates that data breaches require unique detection systems, techniques, and …

Temporal transaction information-aware Ponzi scheme detection for ethereum smart contracts

L Wang, H Cheng, Z Zheng, A Yang, M Xu - Engineering Applications of …, 2023‏ - Elsevier
In recent years, the frenetic advances of blockchain techniques have promoted the large-
scale application of cryptocurrency and attracted significant attention in the mushrooming …

Ethereum Phishing Scam Detection Based on Data Augmentation Method and Hybrid Graph Neural Network Model

Z Chen, SZ Liu, J Huang, YH **u, H Zhang, HX Long - Sensors, 2024‏ - mdpi.com
The rapid advancement of blockchain technology has fueled the prosperity of the
cryptocurrency market. Unfortunately, it has also facilitated certain criminal activities …

BiLSTM4DPS: An attention-based BiLSTM approach for detecting phishing scams in ethereum

M Tang, M Ye, W Chen, D Zhou - Expert Systems with Applications, 2024‏ - Elsevier
With the burgeoning adoption of blockchain technology, cryptocurrencies have surged in
popularity, becoming a focal point of global interest. Concurrently, the emergence of …

Graph Anomaly Detection with Disentangled Prototypical Autoencoder for Phishing Scam Detection in Cryptocurrency Transactions

J Kang, SJ Buu - IEEE Access, 2024‏ - ieeexplore.ieee.org
As the popularity of cryptocurrencies grows, the threat of phishing scams on trading
networks is growing. Detecting unusual transactions within the complex structure of these …

2DynEthNet: A Two-Dimensional Streaming Framework for Ethereum Phishing Scam Detection

J Yang, W Yu, J Wu, D Lin, Z Wu… - IEEE Transactions on …, 2024‏ - ieeexplore.ieee.org
In recent years, phishing scams have emerged as one of the most serious crimes on
Ethereum. Existing phishing scam detection methods typically model public transaction …

Learning to traverse cryptocurrency transaction graphs based on transformer network for phishing scam detection

SH Choi, SJ Buu - Electronics, 2024‏ - mdpi.com
Cryptocurrencies have experienced a surge in popularity, paralleled by an increase in
phishing scams exploiting their transactional networks. Therefore, detecting anomalous …

PSPL: A Ponzi scheme smart contracts detection approach via compressed sensing oversampling-based peephole LSTM

L Wang, H Cheng, Z Sun, A Tian, Z Yang - Future Generation Computer …, 2025‏ - Elsevier
Abstract Decentralized Finance (DeFi) utilizes the key principles of blockchain to improve
the traditional finance system with greater freedom in trade. However, due to the absence of …

TAAD: Time-varying adversarial anomaly detection in dynamic graphs

G Liu, J Zhang, P Lv, C Wang, H Wang… - Information Processing & …, 2025‏ - Elsevier
The timely detection of anomalous nodes that can cause significant harm is essential in real-
world networks. One challenge for anomaly detection in dynamic graphs is the identification …