Bostancı, BeyzanurAlbayrak, Ahmet2023-07-262023-07-262021978-1-6654-0759-5https://doi.org/10.1109/IISEC54230.2021.9672361https://hdl.handle.net/20.500.12684/132822nd International Informatics and Software Engineering Conference (IISEC) - Artificial Intelligence for Digital Transformation -- DEC 16-17, 2021 -- Ankara, TURKEYToday, especially with the emergence of social networks and IoT technologies, big data has entered the literature. With the development of technology, the size of the data has increased and accordingly data security gaps have emerged. In this study, Support Vector Machines and Random Forest algorithms, which are Supervised Machine Learning Algorithms, were used to analyze a data set consisting of unauthorized network logins. As a result of the experimental studies, it was observed that both algorithms produced good results, but the Random Forest approach produced better results.en10.1109/IISEC54230.2021.9672361info:eu-repo/semantics/closedAccessBig Data; Support Vector Machine; Random Forest; Machine LearningBig DataConference Object2-s2.0-85125325170WOS:000841548300013N/A