Thesis Details
Detekce anomálií HTTP aplikací
The goal of this work is to introduce anomaly detection principles and review its possibilities, as one of the intrusion detection methods in HTTP traffic. This work contains theoretical background crucial for performing an anomaly detection on HTTP traffic, and for utilising neural networks in achieving this goal. The work proposes tailored design of an anomaly detection model for concrete web server implementation, describes its implementation and evaluates the results. The result of this work is successful initial experiment, of modeling normal behavior of HTTP traffic and creation of the mechanism, capable of detection of anomalies within future traffic.
anomaly, detection, autoencoders, HTTP, neural, networks
Malinka Kamil, Mgr., Ph.D. (DITS FIT BUT), člen
Ryšavý Ondřej, doc. Ing., Ph.D. (DIFS FIT BUT), člen
Strnadel Josef, Ing., Ph.D. (DCSY FIT BUT), člen
Szőke Igor, Ing., Ph.D. (DCGM FIT BUT), člen
@bachelorsthesis{FITBT23896,
author = "Vlastimil R\'{a}dsetoulal",
type = "Bachelor's thesis",
title = "Detekce anom\'{a}li\'{i} HTTP aplikac\'{i}",
school = "Brno University of Technology, Faculty of Information Technology",
year = 2021,
location = "Brno, CZ",
language = "czech",
url = "https://www.fit.vut.cz/study/thesis/23896/"
}