SSB: Smart Contract Security Detection Tool Suitable for Industrial Control Scenarios

The results of this study highlight the effectiveness of the proposed semantic security detection framework, SSB, in identifying a wide range of vulnerabilities in smart contracts tailored for industrial control scenarios. Compared to existing tools like ZEUS, Securify, and VULTRON, SSB demonstrates...

Full description

Saved in:
Bibliographic Details
Published inSensors (Basel, Switzerland) Vol. 25; no. 15; p. 4695
Main Authors Tao, Ci, He, Shuai, Shen, Xingqiu
Format Journal Article
LanguageEnglish
Published Switzerland MDPI AG 30.07.2025
MDPI
Subjects
Automation
Blockchain
blockchain security
industrial control systems
Large language models
Logic
Ontology
Semantics
Smart contracts
vulnerability detection
industrial control systems
blockchain security
vulnerability detection
smart contracts
Online AccessGet full text

Cover

More Information
Summary:The results of this study highlight the effectiveness of the proposed semantic security detection framework, SSB, in identifying a wide range of vulnerabilities in smart contracts tailored for industrial control scenarios. Compared to existing tools like ZEUS, Securify, and VULTRON, SSB demonstrates superior logical coverage across various vulnerability types, as evidenced by its performance on smart contract samples. This suggests that semantic-based approaches, which integrate domain-specific invariants and runtime monitoring, can address the unique challenges of ICS, such as real-time constraints and semantic consistency between code and physical control logic. The framework’s ability to model industrial invariants—covering security, functionality, consistency, time-related, and resource consumption aspects—provides a robust mechanism to prevent critical errors like unauthorized access or premature equipment operation. However, the lack of real-world ICS validation due to confidentiality constraints limits the generalizability of these findings. Future research should focus on adapting SSB for real industrial deployments, exploring scalability across diverse ICS architectures, and integrating advanced AI techniques for dynamic invariant adjustment. Additionally, addressing cross-chain interoperability and privacy concerns could further enhance the framework’s applicability in complex industrial ecosystems.
Bibliography:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
content type line 23
ISSN:1424-8220
1424-8220
DOI:10.3390/s25154695