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Information System Security Evaluation Algorithm Based on PSO-BP Neural Network.

Qinghua Zheng1

  • 1School of Business, Jinling Institute of Technology, Nanjing 211169, Jiangsu, China.

Computational Intelligence and Neuroscience
|August 30, 2021
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Summary
This summary is machine-generated.

This study enhances information system security by optimizing the BP neural network algorithm with particle swarm optimization (PSO-BP). The improved PSO-BP model demonstrates superior accuracy and faster convergence for intelligent risk assessment.

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Area of Science:

  • Computer Science
  • Information Security
  • Artificial Intelligence

Background:

  • Increasing reliance on information systems necessitates robust security measures.
  • Network attacks pose significant and immeasurable financial and operational risks.
  • Existing security evaluation methods require enhancement to address evolving threats.

Purpose of the Study:

  • To improve the intelligent evaluation of information system security.
  • To develop a more accurate and efficient risk assessment algorithm.
  • To enhance the reliability of information system security through advanced AI techniques.

Main Methods:

  • Optimized the existing BP neural network algorithm for security intelligent evaluation.
  • Implemented particle swarm optimization (PSO) to refine initial BP network parameters.
  • Filtered redundant information to extract core risk factors for improved input node efficiency.

Main Results:

  • The proposed PSO-BP algorithm exhibits faster convergence compared to the traditional BP algorithm.
  • Achieved higher accuracy in predicting risk values with minimal error (average 0.21, max 0.34).
  • Demonstrated consistent performance with near-zero error fluctuations across 100 sample tests.

Conclusions:

  • The PSO-BP algorithm offers excellent performance for information system security risk evaluation.
  • This enhanced approach provides a more reliable and accurate method for intelligent security assessment.
  • The findings highlight the potential of PSO-BP in mitigating risks associated with modern network attacks.