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In the contemporary period characterized by the proliferation of digital technology, individuals are consistently engaged with online resources. Web phishing is a form of social engineering attack in which individuals are deceived by cyber-attackers into divulging crucial login information. As the web evolves beyond English-speaking users, this sort of threat is increasing. A Cyrillic URL is a URL that includes a Cyrillic character with the intention of deceiving ordinary individuals. Cyber attackers transmit Cyrillic URLs by email or chat, prompting individuals to divulge their crucial passwords. This work presents a parsing of the deep web and the creation of a dataset consisting of 1 lakh benign and Cyrillic URLs. We have attained a classification accuracy of 97% by employing Bi-LSTM and have conducted a comparative analysis of different recurrent neural networks.

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Cyrillic URL: A Malicious Website Classification Using Deep Neural Network

  • 会议论文

  • 发表日期：

    2026年

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  • Mainak Sen,
  • Ankan Deria,
  • Soumitra Chatterjee,
  • Snehasish Dey,
  • Debayan Ganguly,
  • Amlan Chakrabarti

摘要

In the contemporary period characterized by the proliferation of digital technology, individuals are consistently engaged with online resources. Web phishing is a form of social engineering attack in which individuals are deceived by cyber-attackers into divulging crucial login information. As the web evolves beyond English-speaking users, this sort of threat is increasing. A Cyrillic URL is a URL that includes a Cyrillic character with the intention of deceiving ordinary individuals. Cyber attackers transmit Cyrillic URLs by email or chat, prompting individuals to divulge their crucial passwords. This work presents a parsing of the deep web and the creation of a dataset consisting of 1 lakh benign and Cyrillic URLs. We have attained a classification accuracy of 97% by employing Bi-LSTM and have conducted a comparative analysis of different recurrent neural networks.