The effectiveness of machine learning in detecting phishing websites

Jacek Łukasz Wilk-Jakubowski; Aleksandra Sikora; Dawid Maciejski

doi:10.35784/iapgos.8143

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Published: Sep 30, 2025

DOI: https://doi.org/10.35784/iapgos.8143

Issue Vol. 15 No. 3 (2025)

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The effectiveness of machine learning in detecting phishing websites
Jacek Łukasz Wilk-Jakubowski, Aleksandra Sikora, Dawid Maciejski

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DOI

https://doi.org/10.35784/iapgos.8143

Authors

Jacek Łukasz Wilk-Jakubowski

jwilk@tu.kielce.pl

Kielce University of Technology, Department of Information Systems, Poland

https://orcid.org/0000-0003-1275-948X

Aleksandra Sikora

asikora@tu.kielce.pl

Kielce University of Technology, Department of Computer Science, Electronics and Electrical Engineering, Poland

Dawid Maciejski

dawidmaciejski0@proton.me

Kielce University of Technology, Faculty of Electrical Engineering, Automatic Control and Computer Science, Poland

https://orcid.org/0009-0003-6426-2552

Abstract

Phishing poses a significant risk in the field of digital security, requiring effective methods for identifying fraudulent websites. This study evaluated the performance of nine machine learning classification models in the context of phishing website detection. Two different input datasets were prepared: the first included the full HTML code, while the second was based on a set of features extracted from that code. The analysis revealed that models trained on the extracted features achieved nearly twice the detection performance compared to those operating on raw HTML code. The use of majority voting further improved classification effectiveness. The study results confirm that proper feature selection and the integration of outputs from multiple models significantly enhance the effectiveness of systems for detecting online threats.

Keywords:

phishing, machine learning, website classification, feature analysis, network security, threat detection

References

[1] Albishri A. A., Dessouky M. M.: A comparative analysis of machine learning techniques for URL phishing detection. Engineering, Technology & Applied Science Research 14(6), 2024, 18495–18501 [https://doi.org/10.48084/etasr.8920]. DOI: https://doi.org/10.48084/etasr.8920

[2] Arvind N.: Phiusiil phishing URL dataset (Version 1) [https://www.kaggle.com/datasets/ndarvind/phiusiil-phishing-url-dataset] (available: 19.03.2025).

[3] Carreras-Coch A., et al.: Communication Technologies in Emergency Situations. Electronics 11(7), 2022, 1155 [https://doi.org/10.3390/electronics11071155]. DOI: https://doi.org/10.3390/electronics11071155

[4] Géron A.: Uczenie maszynowe z użyciem Scikit-Learn, Keras i TensorFlow. Wyd. 3, Helion, 2023.

[5] Hadnagy C., Fincher M., Dreeke R.: Mroczne odmęty phishingu. Nie daj się złowić! Helion, 2018.

[6] Hadnagy C.: Social engineering: the art of human hacking. Wiley Publishing, 2011.

[7] Hastie T., Tibshirani R., Friedman J.: The elements of statistical learning: data mining, inference, and prediction. Springer, 2009. DOI: https://doi.org/10.1007/978-0-387-84858-7

[8] Jha A.: Fight fraud with machine learning. Manning Publications, 2023.

[9] Liu B.: Web data mining: exploring hyperlinks, contents, and usage data. 2nd ed., Springer, 2011. DOI: https://doi.org/10.1007/978-3-642-19460-3

[10] Mitchell R.: Web scraping with Python: collecting data from the modern web. 2nd ed., O’Reilly Media, 2018.

[11] Murphy K.P.: Machine learning: a probabilistic perspective. MIT Press, 2012.

[12] PhishTank: Phishing website database [https://phishtank.org/] (accessed: 22.03.2025).

[13] Reyes-Dorta N., Caballero-Gil P., Rosa-Remedios C.: Detection of malicious URLs using machine learning. Wireless Networks 30, 2024, 7543–7560 [https://doi.org/10.1007/s11276-024-03700-w]. DOI: https://doi.org/10.1007/s11276-024-03700-w

[14] Sasanuma M., et al.: Research and development of very small aperture terminals (VSAT) that can be installed by easy operation during disasters – Issues and the solutions for implementing simple and easy installation of VSAT earth station. IEICE 112(440), 2013, 1–3.

[15] Shalev-Shwartz S., Ben-David S.: Understanding machine learning: from theory to algorithms. Cambridge University Press, 2014. DOI: https://doi.org/10.1017/CBO9781107298019

[16] Shashwat A.: Web page phishing detection dataset (Version 1) [https://www.kaggle.com/datasets/shashwatwork/web-page-phishing-detection-dataset] (available: 23.03.2025).

[17] Suematsu N., et al.: Multi-mode SDR VSAT against big disasters. European Microwave Conference’13, Nuremberg, 2013 [https://doi.org/10.23919/EuMC.2013.6686788].

[18] Tashtoush Y., et al.: Exploring low-level statistical features of n-grams in phishing URLs: a comparative analysis with high-level features. Cluster Computing 27, 2024, 13717–13736 [https://doi.org/10.1007/s10586-024-04655-5]. DOI: https://doi.org/10.1007/s10586-024-04655-5

[19] Wilk-Jakubowski J. Ł.: A review on information systems engineering using VSAT networks and their development directions. Yugoslav Journal of Operations Research 31(3), 2021, 409–428 [https://doi.org/10.2298/YJOR200215015W]. DOI: https://doi.org/10.2298/YJOR200215015W

[20] Wilk-Jakubowski J. Ł.: Broadband satellite data networks in the context of the available protocols and digital platforms. Informatyka, Automatyka, Pomiary w Gospodarce i Ochronie Środowiska – IAPGOŚ 2, 2021, 56–60 [https://doi.org/10.35784/iapgos.2630]. DOI: https://doi.org/10.35784/iapgos.2630

Wilk-Jakubowski, J. Łukasz, Sikora, A., & Maciejski, D. (2025). The effectiveness of machine learning in detecting phishing websites. Informatyka, Automatyka, Pomiary W Gospodarce I Ochronie Środowiska, 15(3), 105–109. https://doi.org/10.35784/iapgos.8143

Author Biographies

Jacek Łukasz Wilk-Jakubowski, Kielce University of Technology, Department of Information Systems

He is an associate professor at the Kielce University of Technology, Faculty of Electrical Engineering, Automatic Control and Computer Science, Department of Information Systems. He was awarded the doctor of technical science degree (with the specialization in ICT, Teleinformatics, Data Transmission and Signal Processing) and doctor of science (habilitation) degree in the Informatics and Computer Science discipline. He is the author of several inventions that have been granted protection by the Patent Office, participant of many national and international conferences and projects, and laureate of several awards, among others for patents. He is the author more than 90 scientific publications (including 5 monographs, 5 chapters in monographs, as well as more than 80 papers).

http://orcid.org/0000-0003-1275-948X

Aleksandra Sikora, Kielce University of Technology, Department of Computer Science, Electronics and Electrical Engineering

She is an assistant professor at the Kielce University of Technology in the Faculty of Electrical Engineering, Automatic Control and Computer Science, Department of Computer Science, Electronics and Electrical Engineering. She has participated in numerous IT projects integrating scientific research with student education in areas such as cybersecurity, big data, machine learning, and digital metrology.

https://orcid.org/0009-0003-6426-2552

Dawid Maciejski, Kielce University of Technology, Faculty of Electrical Engineering, Automatic Control and Computer Science

A graduate of second-cycle studies in Computer Science, specializing in Cybersecurity, at the Faculty of Electrical Engineering, Automation, and Computer Science at the Kielce University of Technology, completed in 2025. His main areas of interest include developing machine learning methods, issues related to computer networks, and user security on the Internet.

The effectiveness of machine learning in detecting phishing websites

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Jacek Łukasz Wilk-Jakubowski, Kielce University of Technology, Department of Information Systems

Aleksandra Sikora, Kielce University of Technology, Department of Computer Science, Electronics and Electrical Engineering

Dawid Maciejski, Kielce University of Technology, Faculty of Electrical Engineering, Automatic Control and Computer Science

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Jacek Łukasz Wilk-Jakubowski, Kielce University of Technology, Department of Information Systems

Aleksandra Sikora, Kielce University of Technology, Department of Computer Science, Electronics and Electrical Engineering

Dawid Maciejski, Kielce University of Technology, Faculty of Electrical Engineering, Automatic Control and Computer Science