Linking Digital Payments to Crime Using Big Data Machine Learning Tools

使用大数据机器学习工具将数字支付与犯罪联系起来

• 批准号: NI210100002
• 负责人: Prof Vallipuram Muthukkumarasamy
• 金额: $ 47.4万
• 依托单位: Griffith University
• 依托单位国家: 澳大利亚
• 项目类别: National Intelligence and Security Discovery Research Grants
• 财政年份: 2021
• 资助国家: 澳大利亚
• 起止时间: 2021-12-30 至 2024-12-29
• 项目状态: 已结题
• 来源: https://dataportal.arc.gov.au/RGS/Web/Grants/NI210100002
• 关键词: Linking; Digital; Payments; Crime; Using

This project aims to automate the process of linking cryptocurrency payments to crime in real time. Cryptocurrencies present a fast-evolving global challenge for crime/ intelligence attribution. The novel investigative toolkit facilitates law enforcement agencies to disrupt suspicious/ ransomware payment. The outcomes include an innovative technique to extract feature vectors to defeat anonymity from multi-blockchain networks; a new machine learning tool to fuse streaming mixed datasets and reconstruct provenance; an attribution mechanism which informs analyst and policy makers to improve national security. This benefits Australia as a world-leader in investigating crypto related criminal activities and creating usable evidence across laws.

该项目旨在实时自动化将加密货币支付与犯罪联系起来的过程。加密货币对犯罪/情报归因提出了快速发展的全球挑战。这个新颖的调查工具有助于执法机构破坏可疑的/勒索软件支付。研究成果包括一种创新技术，用于提取特征向量，以击败多区块链网络中的匿名性；一种新的融合流混合数据集和重建来源的机器学习工具一种为分析人员和政策制定者提供信息以改善国家安全的归因机制。这有利于澳大利亚成为调查加密相关犯罪活动和跨法律创造可用证据的世界领导者。