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An Improved Software Source Code Vulnerability Detection Method: Combination of Multi-Feature Screening and

Xin He1, Asiya1, Daoqi Han1

  • 1College of Computer and Information Engineering, Inner Mongolia Agricultural University, Hohhot 010018, China.

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Summary
This summary is machine-generated.

This study introduces a new model for software vulnerability detection, improving accuracy and reducing training time. The multi-feature screening and integrated sampling model (MFISM) enhances software security by addressing dataset imbalance.

Keywords:
Bi-LSTMabstract syntax tree (AST)integrated oversamplingmulti-feature screeningsource code vulnerability detection

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Area of Science:

  • Computer Science
  • Software Engineering
  • Cybersecurity

Background:

  • Software vulnerability detection is critical for security.
  • Existing methods struggle with imbalanced datasets and lengthy training.
  • Need for efficient and accurate vulnerability detection models.

Purpose of the Study:

  • To introduce the Multi-Feature Screening and Integrated Sampling Model (MFISM) for enhanced software vulnerability detection.
  • To improve the efficiency and accuracy of identifying vulnerabilities in source code.
  • To overcome challenges of class imbalance and long training times in existing models.

Main Methods:

  • Utilized Abstract Syntax Tree (AST) for feature extraction.
  • Applied Analysis of Variance (ANOVA) and feature selection techniques.
  • Implemented integrated over-sampling and outlier detection for data balancing.
  • Employed a Bidirectional Long Short-Term Memory (Bi-LSTM) network for classification.

Main Results:

  • MFISM improved F1 score by approximately 10% over DeepBalance.
  • Reduced model training time to 2-3 hours.
  • Demonstrated superior performance in source code vulnerability detection.

Conclusions:

  • MFISM effectively enhances vulnerability detection accuracy and efficiency.
  • The model successfully addresses class imbalance and reduces training duration.
  • MFISM offers a superior solution for secure software development.