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Malicious Smart Contract Detection ML 2.0

Description

This detection bot detects when a suspicious non-token or non-proxy contract is deployed. It uses an offline trained machine learning model that was built based on contract creation code contained in malicious and benign smart contracts. It will improve upon the previous version.

Model Configuration

Data Used For Training

Algorithm
Given that the malicious contracts are rare, we will use anomaly detection approach for the problem.
Featurization
- [ ] tf-idf using decompiled opcodes as done previously
- [ ] Glove vectors on the decompiled opcodes
ML Models
- [ ] Tree based decision models( Isolation Forest )
- [ ] Word2vec
- [ ] Pretaining with Transformers on unlabelled datasets followed by finetuning on the smaller labelled dataset

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