Smart Learning to Find Dumb Contracts

Explore a groundbreaking conference talk from USENIX Security '23 that introduces Deep Learning Vulnerability Analyzer (DLVA), an innovative tool for detecting vulnerabilities in Ethereum smart contracts. Learn how DLVA leverages powerful deep learning techniques adapted for bytecode analysis, offering a 10-1,000x speedup compared to traditional formal methods-based tools. Discover the three key components of DLVA: Smart Contract to Vector (SC2V), Sibling Detector (SD), and Core Classifier (CC), and understand how they work together to achieve high accuracy in vulnerability detection. Gain insights into DLVA's training algorithm, which extends source code analysis to bytecode without manual feature engineering, and its ability to overcome mislabeled contracts. Compare DLVA's performance against state-of-the-art graph neural networks and other machine learning techniques, and see how it outperforms nine well-known smart contract analysis tools in terms of accuracy and efficiency.