Open Access

ARTICLE

A Data Consistency Insurance Method for Smart Contract

Jing Deng¹, Xiaofei Xing¹, Guoqiang Deng^2,*, Ning Hu³, Shen Su³, Le Wang³, Md Zakirul Alam Bhuiyan⁴

1 School of Computer Science and Cyber Engineering, Guangzhou University, Guangzhou, 510006, China
2 Information Network Engineering and Reasearch Center, South China University of Technology, Guangzhou, 510640, China
3 Cyberspace Institute of Advanced Technology, Guangzhou University, Guangzhou, 510006, China
4 Department of Computer and Information Sciences, Fordham University, New York, 10458, USA

* Corresponding Author: Guoqiang Deng. Email:

Computers, Materials & Continua 2023, 76(3), 3783-3795. https://doi.org/10.32604/cmc.2023.034116

Received 06 July 2022; Accepted 09 November 2022; Issue published 08 October 2023

Abstract

As one of the major threats to the current DeFi (Decentralized Finance) ecosystem, reentrant attack induces data inconsistency of the victim smart contract, enabling attackers to steal on-chain assets from DeFi projects, which could terribly do harm to the confidence of the blockchain investors. However, protecting DeFi projects from the reentrant attack is very difficult, since generating a call loop within the highly automatic DeFi ecosystem could be very practicable. Existing researchers mainly focus on the detection of the reentrant vulnerabilities in the code testing, and no method could promise the non-existent of reentrant vulnerabilities. In this paper, we introduce the database lock mechanism to isolate the correlated smart contract states from other operations in the same contract, so that we can prevent the attackers from abusing the inconsistent smart contract state. Compared to the existing resolutions of front-running, code audit, and modifier, our method guarantees protection results with better flexibility. And we further evaluate our method on a number of de facto reentrant attacks observed from Etherscan. The results prove that our method could efficiently prevent the reentrant attack with less running cost.

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Keywords

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