Juraj Smeriga

Bachelor's thesis

Machine Learning for Phishing URL Detection

Machine Learning for Phishing URL Detection
Abstract:
Zatiaľ čo výskum v oblasti kyberbezpečnosti dosahuje rok čo rok významný pokrok, phishing ako jeden z najrožšírenejších kyberútokov sa nezdá byť na ústupe. Táto práca popisuje spôsob detekcie škodlivých phishingových webstránok pomocou strojového učenia za pomoci atribútov získaných výhradne z URL. Obsahuje popis dostupných dát and proces tvorby atribútov. Popíše výber vhodných algoritmov strojového …more
Abstract:
While research in the field of cybersecurity makes significant year-on-year progress, phishing as one of the most widely used cyberattacks does not seem to be on the retreat. This thesis describes an approach to the detection of malicious phishing websites using machine learning with a focus on using features extracted solely from the URL. It includes the description of available data and the feature …more
 

Keywords

phishing phishing detection malicious URL machine learning k-nearest decision trees SVM Random Forest Naive Bayes classification klasifikácia detekcia phishingu strojové učenie
 
Language used: English
Date on which the thesis was submitted / produced: 26. 5. 2020
Identifier: https://is.muni.cz/th/zc77p/

Thesis defence

  • Date of defence: 24. 6. 2020
  • Supervisor: RNDr. Tomáš Jirsík, Ph.D.
  • Reader: RNDr. Martin Laštovička

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Institution archiving the thesis and making it accessible: Masarykova univerzita, Fakulta informatiky
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Masaryk University

Faculty of Informatics

Bachelor programme / field:
Applied Informatics / Applied Informatics

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