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Heterogeneous Network Representation Learning Approach for Ethereum Identity Identification
IEEE Transactions on Computational Social Systems, 2023Recently, network representation learning has been widely used to mine and analyze network characteristics, and it is also applied to blockchain, but most of the embedding methods in blockchain ignore the heterogeneity of network, so it is difficult to ...
Yixian Wang +3 more
semanticscholar +1 more source
De Computis
Blockchain technology has emerged as a transformative solution for secure, immutable, and decentralized data management across diverse domains, including economics, healthcare, and supply chain management.
Maaz Muhammad Khan +5 more
semanticscholar +1 more source
Blockchain technology has emerged as a transformative solution for secure, immutable, and decentralized data management across diverse domains, including economics, healthcare, and supply chain management.
Maaz Muhammad Khan +5 more
semanticscholar +1 more source
GrabPhisher: Phishing Scams Detection in Ethereum via Temporally Evolving GNNs
IEEE Transactions on Services ComputingPhishing scams are one of Ethereum's most representative security risks that can defraud many transactions in a short period and severely threaten network security.
Jiale Zhang +5 more
semanticscholar +1 more source
TxPhishScope: Towards Detecting and Understanding Transaction-based Phishing on Ethereum
Conference on Computer and Communications Security, 2023The prosperity of Ethereum attracts many users to send transactions and trade crypto assets. However, this has also given rise to a new form of transaction-based phishing scam, named TxPhish.
Bowen He +8 more
semanticscholar +1 more source
Toward Understanding Asset Flows in Crypto Money Laundering Through the Lenses of Ethereum Heists
IEEE Transactions on Information Forensics and SecurityWith the overall momentum of the blockchain industry, financial crimes related to blockchain crypto-assets are becoming increasingly prevalent. After committing a crime, the main goal of cybercriminals is to obfuscate the source of the illicit funds in ...
Jiajing Wu +6 more
semanticscholar +1 more source
Social Science Research Network, 2021
The market for non-fungible tokens (NFTs), transferrable and unique digital assets on public blockchains, has received widespread attention and experienced strong growth since early 2021.
Lennart Ante
semanticscholar +1 more source
The market for non-fungible tokens (NFTs), transferrable and unique digital assets on public blockchains, has received widespread attention and experienced strong growth since early 2021.
Lennart Ante
semanticscholar +1 more source
Fishing for Fraudsters: Uncovering Ethereum Phishing Gangs With Blockchain Data
IEEE Transactions on Information Forensics and SecurityAs one of the most typical cybercrime types, phishing scams have extended the devil’s hand to the emerging blockchain ecosystem in recent years. Especially huge economic losses have been caused by phishing scams in Ethereum, the second-largest blockchain
Jieli Liu +5 more
semanticscholar +1 more source
Ponziguard: Detecting Ponzi Schemes on Ethereum with Contract Runtime Behavior Graph (CRBG)
International Conference on Software EngineeringPonzi schemes, a form of scam, have been discovered in Ethereum smart contracts in recent years, causing massive financial losses. Rule-based detection approaches rely on predefined rules with limited capabilities and domain knowledge dependency ...
Ruichao Liang +6 more
semanticscholar +1 more source