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Correlating IPFIX Records of Proxy Server Traffic
Krůl, Michal ; Jeřábek, Kamil (referee) ; Ryšavý, Ondřej (advisor)
This thesis elabortes the problem of correlation of the network flow records. It tries to find solution, which would allow to automatically correlate flows from both sides of the proxy server. For this purpose, a dataset containing captured network traffic is created, which then serves as a base for analysis. Based on the results of the analysis a solution is presented, which is consequently tested and discussed.
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Detecting JavaScript Code with Known Vulnerabilites
Randýsek, Vojtěch ; Jeřábek, Kamil (referee) ; Polčák, Libor (advisor)
This thesis deals with the detection of vulnerable JavaScript libraries and NPM packages. Based on existing studies, it summarizes the technological core of the Node.js platform and further focuses on selected vulnerabilities of the NPM system and existing means of protection. A Chrome browser extension able to detect and fix JavaScript code with known vulnerabilities on the web browser had been introduced. The tool was tested in a crawl of 50 000 websites. 8 129 vulnerable scripts were detected. The extension has been published to the Chrome Web Store as JS Vulnerability Detector .
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Low Energy GPS Tracker Using LoRa Network
Múčka, Milan ; Jeřábek, Kamil (referee) ; Pluskal, Jan (advisor)
This thesis deals with determine location using very low power consumption device. The main target was to design and construct device using right platform and sensors for localization, sending data using IoT LoRa network and than processing data on server's side. To solve the problem, it was used community network TheThingsNetwork. In thesis I created power efficient device, which can find current location using GPS system and deliver it to user using LoRaWAN network.
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Setup of Application-Computation On-Premise Mini-Cloud Based on Kubernetes
Stuchlý, Samuel ; Ryšavý, Ondřej (referee) ; Jeřábek, Kamil (advisor)
Kubernetes je platforma na orchestráciu kontajnerov, na nasadenie a správu aplikácií v klastri. Cieľom tejto práce je porozumieť kubernetes a jeho komponentom a následne navrhnúť a sprevádzkovať optimálnu architektúru kubernetes klastru pre malý mini-cloud založený na kubernetes v areáli univerzity VUT. Táto bakalárska práca rozoberá základy kontajnerov, runtime kontajnerov, nástroje na orchestráciu kontajnerov, architektúru Kubernetes a jej komponenty a automatizačnú platformu Ansible. Ďalej obsahuje popis navrhnutej architektúry klastra, ktorá bude implementovaná. Príspevok tejto práce spočíva v návrhu architektúry kubernetes klastra, ktorý bude neskôr nasadený na pôde univerzity, pripravený na použitie.
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RQA System Anomaly Detection
Lorenc, Jan ; Jeřábek, Kamil (referee) ; Pluskal, Jan (advisor)
The aim of the theses is to design and implement a machine learning model for anomaly detection in Y Soft's RQA system. Owing to the microservice architecture, an anomaly is considered to be a recurring occurrence of outliers in durations of service requests or a considerable variance in error rate. The thesis outlines the current data collection process in the system and defines what kind of data describe the state of the system. It devises a suitable format of data storage for its subsequent analysis. It presents algorithms commonly used to solve anomaly detection problems. The anomaly detection is designed and implemented using cluster analysis and statistical methods. Finally, the thesis evaluates the quality of the detection and the achieved results.
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Correlating IPFIX Records of Proxy Server Traffic
Krůl, Michal ; Jeřábek, Kamil (referee) ; Ryšavý, Ondřej (advisor)
This thesis elabortes the problem of correlation of the network flow records. It tries to find solution, which would allow to automatically correlate flows from both sides of the proxy server. For this purpose, a dataset containing captured network traffic is created, which then serves as a base for analysis. Based on the results of the analysis a solution is presented, which is consequently tested and discussed.
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Correlating IPFIX Records of Proxy Server Traffic
Krůl, Michal ; Jeřábek, Kamil (referee) ; Ryšavý, Ondřej (advisor)
This thesis engages the problem of correlation the network flow records. It tries to find solution, which would allow to automatically pinpoint correlating flows on both sides of the proxy server. For this purpose, a dataset containing captured network traffic is created, which then serves as a base for analysis. Based on the results of the analysis a solution is presented, which is consequently tested and discussed.
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Detecting JavaScript Code with Known Vulnerabilites
Randýsek, Vojtěch ; Jeřábek, Kamil (referee) ; Polčák, Libor (advisor)
This thesis deals with the detection of vulnerable JavaScript libraries and NPM packages. Based on existing studies, it summarizes the technological core of the Node.js platform and further focuses on selected vulnerabilities of the NPM system and existing means of protection. A Chrome browser extension able to detect and fix JavaScript code with known vulnerabilities on the web browser had been introduced. The tool was tested in a crawl of 50 000 websites. 8 129 vulnerable scripts were detected. The extension has been published to the Chrome Web Store as JS Vulnerability Detector .
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Security System for Web Application Attacks Elimination
Vašek, Dominik ; Zobal, Lukáš (referee) ; Jeřábek, Kamil (advisor)
Nowadays, botnet attacks that aim to overwhelm the network layer by malformed packets and other means are usually mitigated by hardware intrusion detection systems. Application layer botnet attacks, on the other hand, are still a problem. In case of web applications, these attacks contain legitimate traffic that needs to be processed. If enough bots partake in this attack, it can lead to inaccessibility of services provided and other problems, which in turn can lead to financial loss. In this thesis, we propose a detection and mitigation system that can detect botnet attacks in realtime using statistical approach. This system is divided into several modules that together cooperate on the detection and mitigation. These parts can be further expanded. During the testing phase, the system was able to capture approximately 60% of botnet attacks that often focused on spam, login attacks and also DDoS. The number of false positive addresses is below 5%.
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Room Occupancy Detection with IoT Sensors
Kolarčík, Tomáš ; Jeřábek, Kamil (referee) ; Pluskal, Jan (advisor)
The aim of this work was to create a module for home automation tools Home Assistant. The module is able to determine which room is inhabited and estimate more accurate position of people inside the room. Known GPS location cannot be used for this purpose because it is inaccurate inside buildings and therefore one of the indoor location techniques needs to be used. Solution based on Bluetooth Low Energy wireless technology was chosen. The localization technique is the fingerprinting method, which is based on estimating the position according to the signal strength at any point in space, which are compared with a database of these points using machine learning. The system can be supplemented with motion sensors that ensure a quick response when entering the room. This system can be deployed within a house, apartment or small to medium-sized company to determine the position of people in the building and can serve as a very powerful element of home automation.
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