{"total":23,"rows":[{"id":"2306.06108","title":"Demystifying Fraudulent Transactions and Illicit Nodes in the Bitcoin Network for Financial Forensics","created":"2023-05-25","cited_by_count":19,"area":null},{"id":"2104.06559","title":"Identity Inference on Blockchain using Graph Neural Network","created":"2021-04-14","cited_by_count":10,"area":null},{"id":"2405.19383","title":"Network Analytics for Anti-Money Laundering -- A Systematic Literature Review and Experimental Evaluation","created":"2024-05-29","cited_by_count":7,"area":null},{"id":"2204.05746","title":"BABD: A Bitcoin Address Behavior Dataset for Pattern Analysis","created":"2022-04-10","cited_by_count":5,"area":null},{"id":"2206.04803","title":"Detecting Anomalous Cryptocurrency Transactions: an AML/CFT Application of Machine Learning-based Forensics","created":"2022-06-07","cited_by_count":5,"area":null},{"id":"2301.05412","title":"Evolve Path Tracer: Early Detection of Malicious Addresses in Cryptocurrency","created":"2023-01-13","cited_by_count":5,"area":null},{"id":"2309.09972","title":"Artificial Intelligence for Web 3.0: A Comprehensive Survey","created":"2023-08-17","cited_by_count":4,"area":null},{"id":"2402.08593","title":"Graph Feature Preprocessor: Real-time Subgraph-based Feature Extraction for Financial Crime Detection","created":"2024-02-13","cited_by_count":4,"area":null},{"id":"2101.07152","title":"PRESTO: Simple and Scalable Sampling Techniques for the Rigorous Approximation of Temporal Motif Counts","created":"2021-01-18","cited_by_count":3,"area":null},{"id":"2102.08013","title":"Temporal-Amount Snapshot MultiGraph for Ethereum Transaction Tracking","created":"2021-02-16","cited_by_count":3,"area":null},{"id":"2207.07315","title":"Pattern Analysis of Money Flow in the Bitcoin Blockchain","created":"2022-07-15","cited_by_count":2,"area":null},{"id":"2211.14582","title":"Demystifying Bitcoin Address Behavior via Graph Neural Networks","created":"2022-11-26","cited_by_count":2,"area":null},{"id":"2303.02462","title":"Towards Improved Illicit Node Detection with Positive-Unlabelled Learning","created":"2023-03-04","cited_by_count":2,"area":null},{"id":"2309.02460","title":"Effective Illicit Account Detection on Large Cryptocurrency MultiGraphs","created":"2023-09-04","cited_by_count":2,"area":null},{"id":"2404.18251","title":"Machine Learning for Blockchain Data Analysis: Progress and Opportunities","created":"2024-04-28","cited_by_count":2,"area":null},{"id":"2309.15133","title":"From Asset Flow to Status, Action and Intention Discovery: Early Malice Detection in Cryptocurrency","created":"2023-09-26","cited_by_count":1,"area":null},{"id":"2311.17929","title":"New Online Communities: Graph Deep Learning on Anonymous Voting Networks to Identify Sybils in Polycentric Governance","created":"2023-11-25","cited_by_count":1,"area":null},{"id":"2403.17081","title":"Machine Learning on Blockchain Data: A Systematic Mapping Study","created":"2024-03-25","cited_by_count":1,"area":null},{"id":"2501.12491","title":"Optimizing Blockchain Analysis: Tackling Temporality and Scalability with an Incremental Approach with Metropolis-Hastings Random Walks","created":"2025-01-21","cited_by_count":1,"area":null},{"id":"2503.10058","title":"Deep Learning Approaches for Anti-Money Laundering on Mobile Transactions: Review, Framework, and Directions","created":"2025-03-13","cited_by_count":1,"area":null},{"id":"2209.12001","title":"Toward Intention Discovery for Early Malice Detection in Bitcoin","created":"2022-09-24","cited_by_count":0,"area":null},{"id":"2506.04292","title":"GARG-AML against Smurfing: A Scalable and Interpretable Graph-Based Framework for Anti-Money Laundering","created":"2025-06-04","cited_by_count":0,"area":null},{"id":"2506.13173","title":"Efficient Approximate Temporal Triangle Counting in Streaming with Predictions","created":"2025-06-16","cited_by_count":0,"area":null}],"next_cursor":null}