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April 12, 2026INTERNATIONAL JOURNAL OF RESEARCH AND ANALYTICAL REVIEWS0 citationsOpen Access

Adaptive Multi-Modal Phishing Detection Using Transformer Natural Language Processing, Visual Analysis, and Threat Intelligence

KSKorva SandeepBRB. RamjiHRHalavath Rajashekar

Key Points

  • The aim is to develop a multi-modal framework for detecting phishing attacks using various data sources.
  • Utilized transformer-based natural language processing techniques for text analysis.
  • Incorporated visual analysis to identify deceptive elements in phishing attempts.
  • Employed threat intelligence to enhance detection efficacy and adaptability.
  • Achieved improved detection rates compared to traditional methods.
  • Demonstrated effectiveness across diverse phishing scenarios.
  • Showed potential for real-time application in cybersecurity measures.

Abstract

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Cite This Study

Sandeep et al. (2026) studied this question.

synapsesocial.com/papers/69db38274fe01fead37c6602https://doi.org/10.56975/ijrar.v13i1.330555
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