A novel hybrid feature fusion model for detecting phishing scam on Ethereum using deep neural network
T Wen, Y Xiao, A Wang, H Wang - Expert Systems with Applications, 2023 - Elsevier
The development of blockchain technology has brought prosperity to the cryptocurrency
market and has made the blockchain platform a hotbed of crimes. As one of the most …
market and has made the blockchain platform a hotbed of crimes. As one of the most …
A federated learning approach to frequent itemset mining in cyber-physical systems
U Ahmed, G Srivastava, JCW Lin - Journal of Network and Systems …, 2021 - Springer
Effective vector representation has been proven useful for transaction classification and
clustering tasks in Cyber-Physical Systems. Traditional methods use heuristic-based …
clustering tasks in Cyber-Physical Systems. Traditional methods use heuristic-based …
BiLSTM4DPS: An attention-based BiLSTM approach for detecting phishing scams in ethereum
With the burgeoning adoption of blockchain technology, cryptocurrencies have surged in
popularity, becoming a focal point of global interest. Concurrently, the emergence of …
popularity, becoming a focal point of global interest. Concurrently, the emergence of …
Effective identification of similar patients through sequential matching over ICD code embedding
Evidence-based medicine often involves the identification of patients with similar conditions,
which are often captured in ICD (International Classification of Diseases (World Health …
which are often captured in ICD (International Classification of Diseases (World Health …
Embedding for anomaly detection on health insurance claims
Properly analyzing health insurance claims data could lead to significant business insights
and benefits for health service providers and insurance companies. Yet, health insurance …
and benefits for health service providers and insurance companies. Yet, health insurance …
Federated deep active learning for attention-based transaction classification
U Ahmed, JCW Lin, P Fournier-Viger - Applied Intelligence, 2023 - Springer
Cyber-physical transactions can be clustered and classified using an effective vector
representation. Traditionally, methods for finding patterns have relied on heuristics and …
representation. Traditionally, methods for finding patterns have relied on heuristics and …
A phishing account detection model via network embedding for Ethereum
J Luo, J Qin, R Wang, L Li - … on Circuits and Systems II: Express …, 2023 - ieeexplore.ieee.org
As the first blockchain platform to support smart contracts, Ethereum has gained popularity
and breeds various cybercrimes. Many phishing accounts on Ethereum take advantage of …
and breeds various cybercrimes. Many phishing accounts on Ethereum take advantage of …
Category tree distance: a taxonomy-based transaction distance for web user analysis
With the emergence of webpage services, huge amounts of customer transaction data are
flooded in cyberspace, which are getting more and more useful for profiling users and …
flooded in cyberspace, which are getting more and more useful for profiling users and …
Know Your Account: Double Graph Inference-based Account De-anonymization on Ethereum
S Miao, W Qiu, H Zheng, Q Zhang, X Tu, X Liu… - arXiv preprint arXiv …, 2024 - arxiv.org
The scaled Web 3.0 digital economy, represented by decentralized finance (DeFi), has
sparked increasing interest in the past few years, which usually relies on blockchain for …
sparked increasing interest in the past few years, which usually relies on blockchain for …
Con2Vec: Learning embedding representations for contrast sets
Contrast sets are used in many knowledge-based systems to capture data patterns relevant
to a target variable. While they have many advantages such as being highly interpretable …
to a target variable. While they have many advantages such as being highly interpretable …