A novel method for detecting URLs phishing using hybrid machine learning algorithm

Authors

  • Nguyen Manh Thang Academy of Cryptography Techniques
  • Le Quang Anh
  • Hua Song Toan
  • Nguyen Quoc Trung

DOI:

https://doi.org/10.54654/isj.v2i19.978

Keywords:

URL, phishing, SVM, Naive Bayes, machine learning

Tóm tắt

Abstract— The phishing attack is the type of cyberattack that targets people’s trust by masking the malicious intent of the attack as communications from reputable sources. The goal is to steal sensitive data from the victim(s) (banking information, social identification, credentials, etc.) for various purposes (selling for monetary gain, performing identity thief, using as a lever for escalation attack). In 2022, the number of reported phishing attacks will reach a whopping 255 million cases, an increment of 61% compared to 2021. Existing methods of phishing URL detection have limitations. The article proposes a method to increase the accuracy of detecting malicious URL by using machine learning methods Linear Support Vector Classification and multinomial Naive Bayes with voting mechanisms.

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References

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Published

2023-10-11

How to Cite

Thang, N. M., Anh, L. Q., Toan, H. S., & Trung, N. Q. (2023). A novel method for detecting URLs phishing using hybrid machine learning algorithm. Journal of Science and Technology on Information Security, 2(19), 15-28. https://doi.org/10.54654/isj.v2i19.978

Issue

No 2. CS (19) 2023

Section

Papers

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3. Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See The Effect of Open Access).