ABMA Project: Enhancing Smart Contract Security

Overview

The Adaptive Bayesian Metamorphic Assessment (ABMA) introduces a revolutionary approach for enhancing the security of blockchain-based smart contracts. By integrating Bayesian Inference Models with Metamorphic Testing, ABMA stands out as a dynamic and adaptable solution for identifying and mitigating vulnerabilities in smart contracts.

Key Features

• Innovative Framework: Combines Bayesian inference with Metamorphic Testing for comprehensive smart contract security assessment.
• Probabilistic Approach: Employs Bayesian models to effectively manage the uncertainties in vulnerability detection, with a focus on high-risk issues like reentrancy attacks.
• Dynamic Testing: Integrates Metamorphic Testing to adapt to evolving smart contract functions, ensuring relevance and accuracy.
• Empirical Validation: Validated through analysis of 21,116 real-world smart contracts, demonstrating superior performance and real-world applicability.

Repository Contents

1. Data Preprocessing Scripts: Tools and algorithms used for the initial processing of smart contract code, transforming raw data into a format ready for detailed analysis.

2. Feature Selection Algorithms: Scripts implementing Bayesian probabilistic techniques to identify and select key features in smart contracts that are indicative of potential vulnerabilities.

3. Classification and Metamorphic Testing Scripts: Components that combine the insights from feature selection with dynamic metamorphic testing methodologies. This includes mechanisms for classifying contracts based on their vulnerability profiles and identifying zero-day vulnerabilities.

Getting Started

Prerequisites

• Python (version 3.8 or higher)
• Git (for cloning the repository)

Installation

1. Clone the repository:

   git clone https://github.com/niirex1/ABMA-project.git

2. Install required packages:

   pip install -r requirements.txt

3. Run the main script:

   python main.py

Usage Instructions

1. Load Smart Contract Source Code: Begin by importing or loading the source code of the smart contract you wish to analyze.

2. Execute Data Preprocessing Scripts: Run the data preprocessing tools to transform the raw smart contract code into a structured format that is suitable for in-depth analysis.

3. Run Feature Selection Algorithms: Use the feature selection scripts to apply Bayesian probabilistic techniques. This will help in identifying critical features in the smart contract that may indicate vulnerabilities.

4. Perform Classification and Metamorphic Testing: Execute the scripts for classification and metamorphic testing. This process involves classifying the contracts into different vulnerability categories and applying dynamic testing methodologies to uncover potential security issues, including zero-day vulnerabilities.

5. Apply Bayesian Inference and Dynamic Adaptation: Finally, utilize the Bayesian inference scripts for a detailed vulnerability assessment. Update the Bayesian model dynamically based on the outcomes of the metamorphic testing to ensure the model remains accurate and adapts to new patterns and data.

Contributing

We welcome contributions! Here’s how you can contribute:

1. Fork the Repository: Fork the ABMA repository.

2. Clone Your Fork and Create a New Branch:

   git clone https://github.com/your_username/ABMA-project.git
   cd ABMA-project
   git checkout -b feature/your_feature_name

3. Make Changes, Commit, and Push:

   git add .
   git commit -m "Your Commit Message"
   git push origin feature/your_feature_name

4. Submit a Pull Request: Go to your fork on GitHub and create a new pull request.

5. Address Review Comments: Respond to any feedback from maintainers.

See CONTRIBUTING.md for detailed guidelines.

License

ABMA is licensed under the MIT License, allowing commercial use, modification, distribution, and private use. See the LICENSE file for full details.

Contact & Support

• Rexford Sosu: Email, GitHub, LinkedIn

Questions, feedback, or suggestions? Reach out to us!

---