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Enhancing smart contract security using a code representation and GAN based methodology.

Dileep Kumar Murala1, Samia Loucif2, K Vara Prasada Rao3

  • 1Department of Computer Science and Engineering, Faculty of Science and Technology, ICFAI Foundation for Higher Education, Hyderabad, 501203, Telangana, India. drdileepm@ifheindia.org.

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Summary
This summary is machine-generated.

This study introduces a novel Generative Adversarial Network (GAN) method to detect integer overflow vulnerabilities in smart contracts (SCs) before deployment, improving accuracy by 18.1% over existing tools.

Keywords:
Abstract syntax treesBeautyChain (BEC) Token attackBlockchain technologyGenerative adversarial networksProof of weak handSmart contracts

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Area of Science:

  • Computer Science
  • Blockchain Technology
  • Software Engineering

Background:

  • Smart contracts (SCs) on blockchain technology offer transformative business applications but contain critical vulnerabilities.
  • Deployed SCs are immutable, making pre-deployment vulnerability detection essential to prevent financial losses.

Purpose of the Study:

  • To develop an advanced method for proactively identifying integer overflow vulnerabilities in smart contracts.
  • To enhance the accuracy and efficiency of smart contract security analysis.

Main Methods:

  • A novel approach combining code embedding via Abstract Syntax Trees (ASTs) with Generative Adversarial Networks (GANs).
  • Vectorization of SC source code using ASTs to preserve key characteristics beyond traditional analysis.
  • GANs synthesize contract vector data to address data scarcity and improve training.

Main Results:

  • The proposed method effectively detects vulnerabilities using GAN discriminator feedback and cosine/correlation coefficient similarity.
  • Achieved up to an 18.1% improvement in accuracy compared to baseline tools like Oyente and sFuzz.
  • Demonstrated the efficacy of GAN-based proactive analysis for smart contract security.

Conclusions:

  • The GAN-based method offers a significant advancement in detecting smart contract vulnerabilities.
  • Proactive analysis is crucial for securing immutable smart contracts.
  • This approach enhances smart contract security and reliability in blockchain applications.