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RNN and Genetic Algorithms: An Innovative Integration of User Behavior Analysis for Detecting Suspicious Behaviors

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  • Manwella Safar
  • Mohamad Firas Alhalabi

Abstract

In this paper, we propose a hybrid model for user behavior analysis (UBA) and anomaly detection using a gated recurrent units (GRU) and a genetic algorithm (GA) for weight updates. The model went through five stages: First, feature extraction. Second, data normalization and splitting into training and testing datasets. Third, the construction and training of the network to learn normal behavior. Fourth, classification based on the error value and threshold using the test data. Fifth, a comprehensive evaluation of the model. The model was implemented using the Python programming language.

Suggested Citation

  • Manwella Safar & Mohamad Firas Alhalabi, 2025. "RNN and Genetic Algorithms: An Innovative Integration of User Behavior Analysis for Detecting Suspicious Behaviors," Journal of Mathematics, Hindawi, vol. 2025, pages 1-10, December.
    • Handle: RePEc:hin:jjmath:1856065
    DOI: 10.1155/jom/1856065
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