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Detailed analysis of the cybersecurity of photovoltaic systems
Turek, Adam ; Bohačík, Antonín (oponent) ; Mikulášek, Michal (vedoucí práce)
The thesis aims to learn about the methods of attacks on photovoltaic systems and their components. Furthermore, it analyses the different types of photovoltaic systems, individual components, and possible security weaknesses. Furthermore, designing and building a testing workplace that allows monitoring of PV components and network traffic with the implementation of several cyber attacks. The thesis describes the theoretical part of PV systems and their components, as well as cyber security and possible attacks. It also includes an analysis of specific vulnerabilities in PV systems, which was performed through publicly known databases such as Vulners or the National Vulnerability Database. In addition, a description of the Solax and Solinteg inverter test environment, implementation tools, and successfully performed network, Modbus, and cyber analysis on PV inverters with attack simulations.
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Web application for Cybersecurity Job Ads Analysis
Turek, Adam ; Sikora, Marek (oponent) ; Ricci, Sara (vedoucí práce)
The bachelor’s thesis aims to create an interactive global map showing a database of job advertisements in a web application and perform filtering according to various parameters, where machine learning analysis is then performed. The map also shows the number of job advertisements by country. The web application is created using the ReactJS JavaScript library associated with LeafletJS, which provides the main functionality. The machine learning and script change parts are implemented using Python’s programming language. The thesis describes the theoretical part and implementation of individual map functions and deals with the description and successful modification of scripts to perform machine learning.
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Web application for Cybersecurity Job Ads Analysis
Turek, Adam ; Sikora, Marek (oponent) ; Ricci, Sara (vedoucí práce)
The bachelor’s thesis aims to create an interactive global map showing a database of job advertisements in a web application and perform filtering according to various parameters, where machine learning analysis is then performed. The map also shows the number of job advertisements by country. The web application is created using the ReactJS JavaScript library associated with LeafletJS, which provides the main functionality. The machine learning and script change parts are implemented using Python’s programming language. The thesis describes the theoretical part and implementation of individual map functions and deals with the description and successful modification of scripts to perform machine learning.
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