A graph attention network-based multi-agent reinforcement learning framework for robust detection of smart contract vulnerabilities

A graph attention network-based multi-agent reinforcement learning framework for robust detection of smart contract vulnerabilities

Abstract Smart contracts have revolutionized decentralized applications by automating agreement enforcement on blockchain platforms. However, detecting vulnerabilities in smart contract interactions remains challenging due to complex state interdependencies. This paper presents a novel approach usin...

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Bibliographic Details
Main Authors: Philip Kwaku Adjei, Qin Zhiguang, Isaac Amankona Obiri, Ansu Badjie, Christian Nii Aflah Cobblah, Ali Alqahtani, Yeong Hyeon Gu, Mugahed A. Al-antari
Format: Article
Language:English
Published: Nature Portfolio 2025-08-01
Series:Scientific Reports
Subjects:
Smart contract security
Hierarchical reinforcement learning
Graph attention networks
Blockchain vulnerability detection
Predictive analytics
Decentralized application
Online Access:https://doi.org/10.1038/s41598-025-14032-w
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https://doi.org/10.1038/s41598-025-14032-w

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