Cyber Ranges

Cieľom tejto bakalárskej práce je oboznámiť sa so softwarovými nástrojmi používanými pre tvorbu cyber rangov. Tieto nástroje slúžia na simuláciu reálnych kybernetických útokov ofenzívneho a defenzívneho charakteru v bezpečnom a legálnom prostredí. V teoretickej časti sú nástroje rozdelené podľa možných používateľov, dostupných tréningových modelov a účasníckych rolý. Popísaných je niekoľko konkrétných implementácii, zameriavaných na rozličné účely a individuálne riešenia štruktúry stavebných prvkov. Praktickou časťou je porovnanie dostupných softwarových nástrojov pomocou kriterií a výber najviac vyhovujúceho. Pre zvolený nástroj vytvoriť dva plne funkčné scenáre pre piatich používateľov.The goal of this bachelor thesis is to get acquainted with software tools used for creating cyber ranks. These tools are used to simulate real cyber attacks of an offensive and defensive nature in a secure and legal environment. In the theoretical part, the tools are divided according to possible users, available training models and participatory roles. Several specific implementations are described, focused on different purposes and individual solutions of the structure of building elements. The practical part is to compare the available software tools using criteria and select the most suitable. Create two fully functional scenarios for five users for the selected tool.

Cyber Ranges

The goal of this bachelor thesis is to get acquainted with software tools used for creating cyber ranks. These tools are used to simulate real cyber attacks of an offensive and defensive nature in a secure and legal environment. In the theoretical part, the tools are divided according to possible users, available training models and participatory roles. Several specific implementations are described, focused on different purposes and individual solutions of the structure of building elements. The practical part is to compare the available software tools using criteria and select the most suitable. Create two fully functional scenarios for five users for the selected tool

Application of deep learning techniques for anomaly detection in computer networks using graphical representation of network traffic

This thesis deals with the application of deep learning techniques for anomaly detection in computer networks. By selecting appropriate features of the communication network, a graphical representation of the network traffic has been created in order to train convolutional neural networks. The first trained model was used in a Raspberry Pi device with a Neural Compute Stick hardware accelerator. The second model was placed in a central location for additional control of the results. The aim of this work was to design and implement an automated anomaly detection system to be tested by three selected cyber attacks. Evaluate the results obtained and propose optimization options

Application of deep learning techniques for anomaly detection in computer networks using graphical representation of network traffic

Táto diplomová práca sa zaoberá aplikáciou techník hlbokého učenia na detekciu anomálií v počítačových sieťach. Výberom vhodných vlastností komunikačnej siete bola vytvorená grafická reprezentácia sieťovej prevádzky za účelom trénovanie konvolučných neurónových sietí. Prvý natrénovaný model bol použitý v zariadení Raspberry Pi s hardvérovým akcelerátorom Neural Compute Stick. Druhý model bol umiestnený v centrále pre dodatočnú kontrolu výsledkov. Cieľom práce bolo navrhnúť a implementovať automatizovaný systém detekcie anomálií, ktorý bude otestovaný tromi zvolenými kybernetickými útokmi. Vyhodnotiť získané výsledky a navrhnúť možnosti optimalizácie.This thesis deals with the application of deep learning techniques for anomaly detection in computer networks. By selecting appropriate features of the communication network, a graphical representation of the network traffic has been created in order to train convolutional neural networks. The first trained model was used in a Raspberry Pi device with a Neural Compute Stick hardware accelerator. The second model was placed in a central location for additional control of the results. The aim of this work was to design and implement an automated anomaly detection system to be tested by three selected cyber attacks. Evaluate the results obtained and propose optimization options.