POSTER: Multi-Block Fusion Mechanism for Multi-label Vulnerability Detection in Smart Contracts

Van Tong, Cuong Dao, Thep Dong, Hai Anh Tran, Duc Tran, Truong X. Tran

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Ethereum smart contracts offer innovative ways to automate transactions and execute agreements within blockchain systems. However, its inherent complexity can lead to exploitable vulnerabilities. With the advent of large language models, many studies put a special focus on identifying vulnerabilities using these models. Nonetheless, language models are ineffective with the lengthy input sequences. To overcome this limitation, this work proposes a novel multi-label vulnerability detection mechanism using pre-trained language model CodeT5+ combined with a unique multi-block fusion. The results demonstrate that the proposed mechanism can achieve up to 0.998 F1-score and require only 0.39 ms of processing time on a collected dataset comprising 421,266 contracts from Ethereum.

Original languageEnglish (US)
Title of host publicationACM AsiaCCS 2024 - Proceedings of the 19th ACM Asia Conference on Computer and Communications Security
PublisherAssociation for Computing Machinery, Inc
Pages1955-1957
Number of pages3
ISBN (Electronic)9798400704826
DOIs
StatePublished - Jul 1 2024
Event19th ACM Asia Conference on Computer and Communications Security, AsiaCCS 2024 - Singapore, Singapore
Duration: Jul 1 2024Jul 5 2024

Publication series

NameACM AsiaCCS 2024 - Proceedings of the 19th ACM Asia Conference on Computer and Communications Security

Conference

Conference19th ACM Asia Conference on Computer and Communications Security, AsiaCCS 2024
Country/TerritorySingapore
CitySingapore
Period7/1/247/5/24

All Science Journal Classification (ASJC) codes

  • Computational Theory and Mathematics
  • Computer Networks and Communications
  • Computer Science Applications

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