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January 17, 20260 citationsOpen Access

PhishBlocker: An Adaptive Smishing Detection Model Using Machine Learning.

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ACAtul CHOUDHARYRVRenu Vadhera

Key Points

  • To develop a system that detects smishing attacks using adaptive machine learning techniques.
  • Developed a machine learning model for real-time smishing detection.
  • Utilized adaptive algorithms to respond to new phishing patterns.
  • Tested the model for accuracy and effectiveness in various scenarios.
  • Achieved high accuracy in identifying smishing messages.
  • Demonstrated strong adaptability to evolving phishing techniques.

Abstract

Smishing (SMS Phishing) is a rapidly growing cybersecurity threat where attackers use deceptive text messages to trick users into revealing sensitive information. This research presents PhishBlocker, an adaptive machine learning-based system designed to effectively detect and prevent these attacks. The model focuses on real-time adaptation to new phishing patterns, ensuring high accuracy and security for mobile users.

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Cite This Study

CHOUDHARY et al. (2025) studied this question.

synapsesocial.com/papers/696b2616d2a12237a9349632https://doi.org/10.5281/zenodo.18260418
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