Open access
Sep 2026
Comparative evaluation of active learning, random sampling, and deep learning for smart contract vulnerability detection
Smart contracts are widely used to automate blockchain-based transactions and decentralised services, but vulnerabilities in their code can expose users and systems to financial loss, service disruption, and security compromise. Detecting vulnerable smart contracts remains challenging because reliable labelling oft...
G. A. Sampedro, Yan-Hui Cheng, Arlene R. Caballero et al.
· Frontiers in Blockchain · 0 citations