VLDB 2026 Research / reviewers in the wild / expert
Mengjie Ding
dblp:295/3490
· DBLP profile ↗
2ranked-venue papers
1as first author
2since 2021 · last 2022
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Software engineering, systems software and programming languages · 2 · 1 first-author · 2 since 2021
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2022 | A Vulnerability Detection Framework for Hyperledger Fabric Smart Contracts Based on Dynamic and Static AnalysisabstractHyperledger Fabric is another development of blockchain technology after Ethereum, which is more suitable as an operating platform for smart contracts. However, the testing technology of Hyperledger Fabric smart contracts (also known as chaincode) is not yet mature currently. Based on this, this paper studies the vulnerability detection of Golang chaincodes. Firstly, we summarize 17 kinds of Golang chaincode vulnerabilities by investigating existing research. Secondly, taking the high accuracy of dynamic detection and the high efficiency of static detection into consideration, we propose a chaincode vulnerability detection framework that combines the dynamic symbolic execution and the static abstract syntax tree analysis technology. We also implement a supporting-tool that can detect the above 15 types of vulnerabilities. Finally, we test the tool by 15 chaincodes collected from GitHub and unknown vulnerabilities were detected in 13 projects. The precision turned out to be 91% after manual inspection. In order to verify the recall rate, we manually inject 30 vulnerabilities into the collected chaincodes and all of them are detected. The evaluation results show the accuracy of the proposed vulnerability detection method for Hyperledger Fabric smart contracts. Peiru Li, Shanshan Li 0002, Mengjie Ding, Jiapeng Yu, He Zhang 0001, Xin Zhou 0016, Jingyue Li |
EASE | 3 |
| 2021 | HFContractFuzzer: Fuzzing Hyperledger Fabric Smart Contracts for Vulnerability DetectionabstractWith its unique advantages such as decentralization and immutability, blockchain technology has been widely used in various fields in recent years. The smart contract running on the blockchain is also playing an increasingly important role in decentralized application scenarios. Therefore, the automatic detection of security vulnerabilities in smart contracts has become an urgent problem in the application of blockchain technology. Hyperledger Fabric is a smart contract platform based on enterprise-level licensed distributed ledger technology. However, the research on the vulnerability detection technology of Hyperledger Fabric smart contracts is still in its infancy. In this paper, we propose HFContractFuzzer, a method based on Fuzzing technology to detect Hyperledger Fabric smart contracts, which combines a Fuzzing tool for golang named go-fuzz and smart contracts written by golang. We use HFContractFuzzer to detect vulnerabilities in five contracts from typical sources and discover that four of them have security vulnerabilities, proving the effectiveness of the proposed method. Mengjie Ding, Peiru Li, Shanshan Li 0002, He Zhang 0001 |
EASE | 1 |