A Data Consistency Insurance Method for Smart Contract
Source abstract
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.
Source: openalex_inverted_index · Quality: baseline
Research context
OpenAlex topics: Blockchain Technology Applications and Security · Cloud Data Security Solutions · FinTech, Crowdfunding, Digital Finance
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
References (17)
Show source-provided references
1. AutoD: Intelligent blockchain application unpacking based on JNI layer deception call10.1109/MNET.011.2000467 ↗
2. V. Buterin, “Ethereum whitepaper,” 2014. [Online]. Available: https://ethereum.org/en/whitepaper/
3. A runtime information based defense technique for Ethereum smart contract
4. H. Kamarul, “Ethereum in 2020: The view from the block explorer,” 2021. [Online]. Available: https://medium.com/etherscan-blog/ethereum-in-2020-the-view-from-the-block-explorer-2f9a1db2ee15
5. V. Buterin, “CRITICAL UPDATE Re: DAO Vulnerability,” 2016. [Online]. Available: https://blog.ethereum.org/2016/06/17/critical-update-re-dao-vulnerability/
6. Towards automated reentrancy detection for smart contracts based on sequential models10.1109/ACCESS.2020.2969429 ↗
7. ReGuard: Finding reentrancy bugs in smart contracts
8. Reentrancy vulnerability identification in Ethereum smart contracts
9. Ægis: Shielding vulnerable smart contracts against attacks
10. F. Giordano and A. Bachfischer, “OpenZeppelin-Contracts,” 2021. [Online]. Available: https://github.com/OpenZeppelin/openzeppelin-contracts
11. Healthchain: Secure EMRs management and trading in distributed healthcare service system10.1109/JIOT.2020.3038721 ↗
12. A certificateless signcryption mechanism based on blockchain for edge computing
13. Efficient medical Big Data management with keyword-searchable encryption in healthchain10.1109/JSYST.2022.3173538 ↗
14. Block-DEF: A secure digital evidence framework using blockchain10.1016/j.ins.2019.04.011 ↗
15. Sereum: Protecting existing smart contracts against Re-entrancy attacks
16. Smart contracts: Security patterns in the Ethereum ecosystem and solidity
17. An efficient anti-quantum lattice-based blind signature for blockchain-enabled systems10.1016/j.ins.2020.08.032 ↗