The rise of Blockchain have provide certain advantages to the field of financial technology, with the application of cryptocurrency such as Bitcoin and Ethereum, the cross-border payment could be more convenient and reducing transaction cost.  However, due to the pseudo-anonymous nature of cryptocurrency, this technology become highly popular and presented in criminal activities. This has increase the difficulties in tracing and forensics. Therefore, the detection and tracing of illegal activities within blockchain is important.

To improve and increase the efficiency of detecting and identify suspicious or malicious activities in blockchain, especially cryptocurrency, an AI-Driven Blockchain Forensics application would be proposed to identify phishing account and tracing fraudulent or illicit activities on the blockchain. In addition, the application would visualize the risks, transaction history and features of the specific account. The project will leverage machine learning algorithms to enable automated analysis of existing blockchain data from specific account. The tool will focus on identifying anomalies, patterns, and correlations that can indicate potential fraudulent transactions, money laundering, or other illicit activities. The deliverables shall include mobile, web application and machine learning model.