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Methods for Realtime Voice Deepfakes Creation
Alakaev, Kambulat ; Pleško, Filip (oponent) ; Malinka, Kamil (vedoucí práce)
This thesis explores the possibility of achieving real-time voice deepfake generation using open-source tools. Through experiments, it was discovered that the generation rate of voice deepfakes is affected by the computing power of the devices running the speech creation tools. A deep learning model was identified to be capable of generating speech in near real time. However, limitations in the tool containing this model prevented continuous input data for real-time generation. To address this, a program was developed to overcome these limitations. The quality of the generated deepfakes was evaluated using both voice deepfake detection models and human online surveys. The results revealed that while the model could deceive detection models, it was not successful in fooling humans. This research highlights the accessibility of open-source voice synthesis tools and the potential for their misuse by individuals for fraudulent purposes.
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Cyber security analysis of photovoltaic systems for apartment buildings
Škoviera, Tomáš ; Kohout, David (oponent) ; Mikulášek, Michal (vedoucí práce)
This bachelor thesis focuses on the security problem of a photovoltaic power plant, which is connected to the internet in order to configure it and remotely monitor statistics on electricity production and consumption. A photovoltaic system with an inverter from a selected company with parameters suitable for a small apartment building or a similarly sized building was analyzed. The main objective of the work is to analyze the communication interfaces and protocols through which the inverter communicates, in order to determine whether it is safe from a cybersecurity point of view to have such a system connected to the Internet. The work also includes performing several flooding attacks on the inverter to see if the inverter is able to detect that it is under attack and defend against it appropriately.
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Securing IoT applications with Arm Cortex-M33 microcontrollers
Tonka, Marek ; Zeman, Václav (oponent) ; Slavíček, Karel (vedoucí práce)
The bachelor thesis analyses the characteristics of modern microcontrollers with ARM Cortex-M33 architecture and their contribution to securing IoT applications. The theoretical part focuses on the introduction of ARM along with the characteristic of the ARMv8 architecture on which the Cortex-M33 processors are built. Emphasis is also placed on the introduction of the new TrustZone technology, which is a key security feature of these processors. Subsequently, a selection of microcontrollers and their features from five leading semiconductor companies is presented. The practical part covers the installation and setup of the two IDEs for the following work with the NUCLEO-575-ZI-Q and LPC55S69-EVK boards. Based on these development boards, four unique features are tested to demonstrate the benefits of using ARM processors to secure IoT applications.
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Diffusion Models and their Impact on Cybersecurity
Dvorščák, Patrik ; Homoliak, Ivan (oponent) ; Lapšanský, Tomáš (vedoucí práce)
This thesis explores the performance of diffusion models (DMs) and generative adversarial networks (GANs) in creating AI-generated visual content across multiple applications, including face synthesis, text-to-image generation, artistic rendering, image-to-image translation, video synthesis, and super-resolution. Through comparative experiments, this research evaluates the models' ability to generate detailed, realistic, and artistically compelling visuals from textual and image prompts. The results reveal that DMs excel in producing highly detailed images that closely follow text prompts, particularly effective in face synthesis and text-to-image tasks. In contrast, GANs are more adept at rendering realistic environmental scenes, suitable for applications requiring immersive visuals. Both model types are competent in artistic rendering, though they differ in style adaptation and creativity. The thesis concludes with future research directions aimed at enhancing model efficacy and integrating these technologies more effectively into practical applications.
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Optimization of Classification Models for Malicious Domain Detection
Pouč, Petr ; Jeřábek, Kamil (oponent) ; Hranický, Radek (vedoucí práce)
This thesis focuses on the development of advanced methods for malicious domain name detection using optimization techniques in machine learning. The thesis investigates and evaluates the effectiveness of different optimization strategies for classification. As evaluation tools, I selected classification algorithms that differ in their approach, including deep learning, decision tree techniques, or hyperplane search. These methods are investigated in terms of their ability to effectively classify domain names depending on the implemented optimization techniques. Optimization strategies include the creation of ground-truth datasets, application of data processing methods, advanced feature selection, solving the class imbalance problem, and hyperparameter tuning. The final part of the paper presents a detailed analysis of the benefits of each optimization approach. The experimental part of the study demonstrates exceptional results by combining several methodologies. The top CNN models obtained up to 0.9926 F1 while lowering FPR to 0.3%. The contribution of this study is to provide specific methodologies and tactics for the successful identification of malicious domain names in the cybersecurity area.
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Poloautomatická klasifikace podezřelých URL a jejich detekce v síťovém provozu
Novotná, Michaela ; Poliakov, Daniel (oponent) ; Žádník, Martin (vedoucí práce)
Tato práce se zaměřuje na návrh a implementaci systému pro detekci a analýzu potenciálně škodlivých URL adres v síťovém provozu. Systém zahrnuje proces získávání podezřelých URL adres z honeypotů, automatickou analýzu URL adres, která zahrnuje také proces klasifikace. Dále se systém zaměřuje na manuální klasifikaci prostřednictvím webového rozhraní, které je navrženo zároveň i pro procházení dat získaných v průběhu automatické analýzy. Další část systému představují detekční a reportovací moduly pro systém NEMEA, které zajišťují detekci škodlivých adres v síťovém provozu. Systém se zaměřuje na získávání informací o kybernetických hrozbách a jejich sdílení s veřejností prostřednictvím platforem MISP a URLhaus. Po úspěšném testování byl systém nasazen v prostředí sítě CESNET a předán bezpečnostnímu oddělení organizace.
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Raising Users' Security Awareness of Deepfakes Attacks
Novák, David ; Šalko, Milan (oponent) ; Malinka, Kamil (vedoucí práce)
This thesis provides a general overview of deepfakes, what they are, how they may be used or misused, and an introduction to cybersecurity education, especially concerning deepfakes attacks. The thesis aims to provide a way for users to enhance their awareness of security issues related to deepfake attacks. The work represents my design and implementation of a web-based application pursuing this aim, based on the summary of research concerning deepfakes. The solution offers users options to both learn about deepfakes and experience the creation of deepfakes in a simplified way. The testing of users before and after experiencing my platform indicated an increase in users' knowledge by up to 85.9\,\%. The data indicate both general user inexperience and a lack of understanding of deepfakes, which is problematic in today's trend to use deepfakes for cyber-attacks. However, based on the results, my application can fill this gap in crucial security knowledge.
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Post-quantum Secure Communication in IoT
Goldshtein, Daniil ; Ricci, Sara (oponent) ; Malina, Lukáš (vedoucí práce)
This work concentrates on the current state of Post-Quantum cryptography and it's applicability on the resource-limited environment of Internet of Things. In theoretical part, it briefly describes currently known types of Post-Quantum algorithms and analyses their best implementations either already recommended, or the ones closest to be selected for further standardization. It also focuses on existing challenges and limitations regarding Internet of Things. The practical part of this thesis is dedicated to the comparison of multiple libraries in terms of their modularity, resource efficiency, support and performance on operating with standardized Post-Quantum algorithms. It is then dedicated to the implementation providing authencity of data with the help of quantum resistant digital signatures, as well as its encryption. The results of all tests are systemized in tables. The conclusion of this thesis contains final analysis and summarizes the results achieved with the developed framework.
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Vyhodnocení kvality a dostupnosti zdrojů obrazových médií pro tvorbu deepfakes
Andrýsek, Kryštof ; Malinka, Kamil (oponent) ; Firc, Anton (vedoucí práce)
Umělá inteligence je v posledních letech na vzestupu a začíná se stávat běžnou součástí našich životů. Tato práce se zaměřuje na nebezpečí související s obrazovými deepfakes. V současnosti se totiž ukazuje, že se netýká pouze vysoce postavených politických osobností nebo hollywoodských hvězd, ale může ovlivnit život kohokoliv z nás. K tomu přispívá mimo jiné zvyšující se množství aplikací, s jejichž pomocí dokáže deepfake vytvořit i člověk bez odborných znalostí a zkušeností. Primárním úkolem této práce je vyhodnotit zdroje, které lze využít k získání obrazových médií vhodných pro tvorbu obličejových deepfakes, a navrhnout metody, pomocí nichž je možné zhodnotit kvalitu těchto zdrojů z pohledu vhodnosti pro tvorbu deepfakes. Další cíl představuje identifikace skupin lidí, jimž hrozí vyšší riziko v souvislosti s obrazovými deepfakes, což může napomoci dokonalejší prevenci a obecnému prohloubení znalostí. Práce nabízí rozbor zdrojů použitelných k tvorbě obličejových deepfakes, navrhuje metody hodnocení jejich kvality, detailní vyhodnocení zdrojů pomocí těchto metod a analýzu zranitelnosti jednotlivých skupin osob. Nakonec je pomocí dotazníkového šetření, zaměřeného především na zdroj sociální sítě, zkoumáno, v jakém množství a jaký druh fotografií sdílejí běžní uživatelé nejčastěji, a na základě těchto údajů jsou upřesněny informace o rizikových skupinách.
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Modular Application for the Management of Cyber Polygons
Janek, Samuel ; Rychlý, Marek (oponent) ; Hranický, Radek (vedoucí práce)
The goal of this work is the design and development of version 2.0 of the Brno University of Technology Cyber Arena (BUTCA) platform. The BUTCA platform is used for cybersecurity training. The reason for the creation of this work are new requirements that require extensive changes in the core of the platform itself. For this reason, a part of this work is dedicated to the reimplementation and subsequent expansion of the existing system. In order to meet some of the new requirements, the platform is extended with an authentication server (AS), which is implemented as a separate application. Both the AS and the platform use a client-server architecture, with the server part being implemented as a web API and the client part as a Single-Page Application (SPA). The implementation of this work will expand the use of the platform among institutions, which, in the case of version 1.0, would have problem with processing of their sensitive data by external institution.
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