Securing and Lightweighting Smart Contracts Based on Multiple Network Structures

Abstract

Smart contracts, as a core component of blockchain technology, face significant challenges such as privacy leakage, poor security, and substantial computational and storage requirements. This study addresses these issues through deep learning and lightweight network structures. Firstly, a method employing deep learning networks for black-boxing is proposed, effectively enhancing the security and privacy protection of smart contracts. Secondly, a lightweight network structure is designed to successfully reduce the consumption of computational and storage resources. Lastly, comparative analysis with traditional methods demonstrates the superior performance of this approach in smart contract encryption, highlighting its effectiveness in addressing key security and efficiency concerns. This innovative solution not only improves the robustness of smart contracts but also makes them more practical for widespread use by mitigating resource-intensive demands.