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The use of federated learning in the field of security on Android OS
Szüč, Martin ; Myška, Vojtěch (oponent) ; Michálek, Jakub (vedoucí práce)
This thesis explores the use of federated learning in the context of cybersecurity, specifically in detecting phishing attacks via email on the Android operating system. The~theoretical part of the thesis deals with concepts of federated learning, machine learning, and various phishing techniques. The main goal of the practical part is to design and implement a mobile application that uses federated learning to train machine learning models. This application is designed to detect phishing emails while ensuring that the content of the emails is not sent to a central server, thereby protecting users' sensitive data. The~thesis includes the design of the application architecture, integration of Python modules, processing and classification of emails, and implementation of federated learning. The results of the application testing demonstrate the effectiveness of the proposed solution in detecting phishing attacks while also highlighting the privacy benefits provided by federated learning.

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