Thesis Details
Analýza anomálií v uživatelském chování
The aim of this work is to create an application that allows modeling of user behavior and subsequent search for anomalies in this behavior. An application entry is a list of actions the user has executed on his workstation. From this information and from information about the events that occurred on this device the behavioral model for a specific time is created. Subsequently, this model is compared to models in different time periods or with other users' models. From this comparison, we can get additional information about user behavior and also detect anomalous behavior. The information about the anomalies is useful to build security software that prevents valuable data from being stolen (from the corporate enviroment).
User Behavior Analysis, Data Mining, Anomaly detection, Machine learning
Čadík Martin, doc. Ing., Ph.D. (DCGM FIT BUT), člen
Holub Jan, prof. Ing., Ph.D. (FIT CTU), člen
Křivka Zbyněk, Ing., Ph.D. (DIFS FIT BUT), člen
Polčák Libor, Ing., Ph.D. (DIFS FIT BUT), člen
Szőke Igor, Ing., Ph.D. (DCGM FIT BUT), člen
@mastersthesis{FITMT21474,
author = "Luk\'{a}\v{s} Petrovi\v{c}",
type = "Master's thesis",
title = "Anal\'{y}za anom\'{a}li\'{i} v u\v{z}ivatelsk\'{e}m chov\'{a}n\'{i}",
school = "Brno University of Technology, Faculty of Information Technology",
year = 2019,
location = "Brno, CZ",
language = "czech",
url = "https://www.fit.vut.cz/study/thesis/21474/"
}