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October 5, 2025Journal of Mobile MultimediaOpen Access

Whale Optimization and AutoML for Precise Phishing Detection

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Authors

DSDivya SinghalAVAnkit VermaRGRadhakrishnan Gopalapillai

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Overview

This study examines machine learning algorithms for phishing detection, suggesting that optimized feature selection enhances cyberattack identification.

Key Points

  • The study achieved an R2 value of 0.9534, indicating strong accuracy in phishing detection.
  • Using the whale optimization algorithm for feature selection improved the model's efficacy against phishing attacks.
  • Real-time fraud protection is essential due to the evolving tactics employed by phishing attackers.
  • The regression-based assessment method demonstrated significantly low prediction errors with RMSE of 0.1079.

Cite This Study

Singhal et al. (2025) studied this question.

synapsesocial.com/papers/68e24e6fd6d66a53c2473c4ahttps://doi.org/10.13052/jmm1550-4646.2153
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