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Dissertations / Theses on the topic 'Deepfakes'

Author: Grafiati
Published: 4 June 2021
Last updated: 27 July 2025

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1

Wardh, Eric, and Victor Wirstam. "Deepfakes - En risk för samhället?" Thesis, Högskolan i Halmstad, Akademin för informationsteknologi, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:hh:diva-44904.

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En deepfake kan vara allt från en bild, video eller ljudklipp, manipulerad med hjälp av AI-teknologi. Deepfakes används legitimt i exempelvis spel- och filmindustrin, men det vanligaste användningsområdet för deepfakes är att skapa manipulerade bilder, videor eller ljudklipp för att sprida felaktig information. Ett annat användningsområde är för att få det att se ut som att personer som egentligen inte medverkat i den aktuella bilden, videon eller ljudklippet faktiskt har gjort det. Denna uppsats fokuserar på att undersöka hur deepfakes används och hur de kan användas för att påverka samhället
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2

Björklund, Christoffer. "Deepfakes inom social engineering och brottsutredningar." Thesis, Högskolan i Halmstad, Akademin för informationsteknologi, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:hh:diva-42373.

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”Deepfake” är en förkortning av ”deep learning” och ”fake”. Deepfakes är syntetisk audiovisuell media som använder sig av maskininlärning för att generera falska videoklipp, bilder och/eller ljudklipp. Detta projekt fokuserar på deepfakes inom förfalskat videomaterial, där en persons ansikte i en video är utbytt mot en annan persons ansikte. Fokuset för den här rapporten är att undersöka hur enkelt det är att göra en egen deepfake med grundläggande kunskap. Detta är gjort med ett experiment som avser att mäta kvantitativa och kvalitativa resultat från intervjuer. Intervjuobjekten har tittat på
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3

Firc, Anton. "Použitelnost Deepfakes v oblasti kybernetické bezpečnosti." Master's thesis, Vysoké učení technické v Brně. Fakulta informačních technologií, 2021. http://www.nusl.cz/ntk/nusl-445534.

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Deepfake technológia je v poslednej dobe na vzostupe. Vzniká mnoho techník a nástrojov pre tvorbu deepfake médií a začínajú sa používať ako pre nezákonné tak aj pre prospešné činnosti. Nezákonné použitie vedie k výskumu techník pre detekciu deepfake médií a ich neustálemu zlepšovaniu, takisto ako k potrebe vzdelávať širokú verejnosť o nástrahách, ktoré táto technológia prináša. Jedna z málo preskúmaných oblastí škodlivého použitia je používanie deepfake pre oklamanie systémov hlasovej autentifikácie. Názory spoločnosti na vykonateľnosť takýchto útokov sa líšia, no existuje len málo vedeckých d
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Gardner, Angelica. "Stronger Together? An Ensemble of CNNs for Deepfakes Detection." Thesis, Linnéuniversitetet, Institutionen för datavetenskap och medieteknik (DM), 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:lnu:diva-97643.

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Deepfakes technology is a face swap technique that enables anyone to replace faces in a video, with highly realistic results. Despite its usefulness, if used maliciously, this technique can have a significant impact on society, for instance, through the spreading of fake news or cyberbullying. This makes the ability of deepfakes detection a problem of utmost importance. In this paper, I tackle the problem of deepfakes detection by identifying deepfakes forgeries in video sequences. Inspired by the state-of-the-art, I study the ensembling of different machine learning solutions built on convolu
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Wang, Xueyu. "DeepFake's Adversary: Disrupting DeepFake by Perturbations." Thesis, The University of Sydney, 2022. https://hdl.handle.net/2123/28642.

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In recent years, with the advances of generative models, many powerful face manipulation systems have been developed based on Deep Neural Networks (DNNs), called DeepFakes. If DeepFakes are not controlled timely and properly, they would cause severe social impact and become a real threat to not only celebrities but also ordinary people. One way to defend the DeepFake is to disrupt the DeepFake generation by adding human-imperceptible perturbations to source inputs. Adding perturbations to the source inputs will make DeepFake results distorted from the perspective of human eyes. However, the ex
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6

Fontanella, Simone. "Rassegna degli strumenti per la creazione e l'individuazione di Deepfakes." Bachelor's thesis, Alma Mater Studiorum - Università di Bologna, 2021. http://amslaurea.unibo.it/23156/.

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Questo volume di tesi descrive lo studio di una nuova tecnologia basata sull'intelligenza artificiale e l'apprendimento automatico nota con il nome di Deepfake. I deepfake nascono per manipolare il volto di una persona in una foto o in un video, attraverso dei modelli matematici noti come reti neurali artificiali. Il primo a fare uso di Deepfake fu un utente Reddit che voleva scambiare i volti delle attrici in video per adulti. I target di questa tecnologia sono spesso attori o personaggi famosi, visto la facilità e la quantità con cui possiamo reperire foto e video che li ritraggono. Sebbene
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7

Inevik, Mina. "Skenet bedrar: Fake porn i svensk straffrätt." Thesis, Uppsala universitet, Juridiska institutionen, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-444204.

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Sedan år 2017 har många internetanvändare fått bekanta sig med fenomenet deepfakes som är en slags digital imitation där en persons ansikte kan fogas samman med en annan persons kropp. Så kallade face swap-appar och filter är inget nytt men det som särskiljer deepfakes är att de skapas med hjälp av artificiell intelligens som kan ge extremt verk- liga resultat. Dessutom blir tekniken allt mer avancerad och lättillgänglig för gemene man, vilket innebär större risk för att den missbrukas t.ex. för att skapa fake porn där en persons ansikte infogas i en existerande bild med sex
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8

Fjellström, Lisa. "The Contribution of Visual Explanations in Forensic Investigations of Deepfake Video : An Evaluation." Thesis, Umeå universitet, Institutionen för datavetenskap, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-184671.

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Videos manipulated by machine learning have rapidly increased online in the past years. So called deepfakes can depict people who never participated in a video recording by transposing their faces onto others in it. This raises the concern of authenticity of media, which demand for higher performing detection methods in forensics. Introduction of AI detectors have been of interest, but is held back today by their lack of interpretability. The objective of this thesis was therefore to examine what the explainable AI method local interpretable model-agnostic explanations (LIME) could contribute
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9

Hasanaj, Enis, Albert Aveler, and William Söder. "Cooperative edge deepfake detection." Thesis, Jönköping University, JTH, Avdelningen för datateknik och informatik, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:hj:diva-53790.

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Deepfakes are an emerging problem in social media and for celebrities and political profiles, it can be devastating to their reputation if the technology ends up in the wrong hands. Creating deepfakes is becoming increasingly easy. Attempts have been made at detecting whether a face in an image is real or not but training these machine learning models can be a very time-consuming process. This research proposes a solution to training deepfake detection models cooperatively on the edge. This is done in order to evaluate if the training process, among other things, can be made more efficient wit
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10

Spinato, Claudia <1995&gt. "Arte e intelligenza artificiale nell'era dei deepfake." Master's Degree Thesis, Università Ca' Foscari Venezia, 2021. http://hdl.handle.net/10579/20119.

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Con lo sviluppo dell’intelligenza artificiale e dei nuovi media diventa sempre più difficile al giorno d’oggi orientarsi nel mondo digitale e della disinformazione. Il confine tra realtà e illusione è labile: i deepfake nell’ultimo decennio sono un pericolo sempre maggiore e spesso difficile da riconoscere. L’elaborato, basandosi sul concetto di iperrealismo secondo alcuni principali filosofi e affrontando il problema filosofico della distinzione tra immagine e realtà, ne segue lo sviluppo attraverso la nascita dei deepfake e dell’intelligenza artificiale (nello specifico delle GANs), individu
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Emir, Alkazhami. "Facial Identity Embeddings for Deepfake Detection in Videos." Thesis, Linköpings universitet, Datorseende, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-170587.

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Forged videos of swapped faces, so-called deepfakes, have gained a  lot  of  attention in recent years. Methods for automated detection of this type of manipulation are also seeing rapid progress in their development. The purpose of this thesis work is to evaluate the possibility and effectiveness of using deep embeddings from facial recognition networks as base for detection of such deepfakes. In addition, the thesis aims to answer whether or not the identity embeddings contain information that can be used for detection while analyzed over time and if it is suitable to include information abo
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12

GUARNERA, LUCA. "Discovering Fingerprints for Deepfake Detection and Multimedia-Enhanced Forensic Investigations." Doctoral thesis, Università degli studi di Catania, 2021. http://hdl.handle.net/20.500.11769/539620.

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Forensic Science, which concerns the application of technical and scientific methods to justice, investigation and evidence discovery, has evolved over the years to the birth of several fields such as Multimedia Forensics, which involves the analysis of digital images, video and audio contents. Multimedia data was (and still is), altered using common editing tools such as Photoshop and GIMP. Rapid advances in Deep Learning have opened up the possibility of creating sophisticated algorithms capable of manipulating images, video and audio in a “simple” manner causing the emergence of a powerful
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13

Tak, Hemlata. "End-to-End Modeling for Speech Spoofing and Deepfake Detection." Electronic Thesis or Diss., Sorbonne université, 2023. https://accesdistant.sorbonne-universite.fr/login?url=https://theses-intra.sorbonne-universite.fr/2023SORUS104.pdf.

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Les systèmes biométriques vocaux sont utilisés dans diverses applications pour une authentification sécurisée. Toutefois, ces systèmes sont vulnérables aux attaques par usurpation d'identité. Il est donc nécessaire de disposer de techniques de détection plus robustes. Cette thèse propose de nouvelles techniques de détection fiables et efficaces contre les attaques invisibles. La première contribution est un ensemble non linéaire de classificateurs de sous-bandes utilisant chacun un modèle de mélange gaussien. Des résultats compétitifs montrent que les modèles qui apprennent des indices discrim
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Weidenstolpe, Louise, and Jade Jönsson. "Manipulation i rörligt format - En studie kring deepfake video och dess påverkan." Thesis, Malmö universitet, Fakulteten för teknik och samhälle (TS), 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:mau:diva-20573.

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Med deepfake-teknologi kan det skapas manipulerade videor där det produceras falska bilder och ljud som framställs vara verkliga. Deepfake-teknologin förbättras ständigt och det kommer att bli svårare att upptäcka manipulerade videor online. Detta kan innebära att en stor del mediekonsumenter omedvetet exponeras för tekniken när de använder sociala medier. Studiens syfte är att undersöka unga vuxnas medvetenhet, synsätt och påverkan av deepfake videor. Detta eftersom deepfake-teknologin förbättras årligen och problemen med tekniken växer samt kan få negativa konsekvenser i framtiden om den utn
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Jönsson, Jade, and louise weidenstolpe. "Manipulation i rörligt format - En studie kring deepfake video och dess påverkan." Thesis, Malmö universitet, Fakulteten för teknik och samhälle (TS), 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:mau:diva-20776.

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Med deepfake-teknologi kan det skapas manipulerade videor där det produceras falska bilder och ljud som framställs vara verkliga. Deepfake-teknologin förbättras ständigt och det kommer att bli svårare att upptäcka manipulerade videor online. Detta kan innebära att en stor del mediekonsumenter omedvetet exponeras för tekniken när de använder sociala medier. Studiens syfte är att undersöka unga vuxnas medvetenhet, synsätt och påverkan av deepfake videor. Detta eftersom deepfake-teknologin förbättras årligen och problemen med tekniken växer samt kan få negativa konsekvenser i framtiden om den utn
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16

Huang, Jiajun. "Learning to Detect Compressed Facial Animation Forgery Data with Contrastive Learning." Thesis, The University of Sydney, 2022. https://hdl.handle.net/2123/29183.

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The facial forgery generation, which could be utilised to modify facial attributes, is the critical threat to digital society. The recent Deep Nerual Network based forgery generation methods, called Deepfake, can generate high quality results that are hard to be distinguished by human eyes. Various detection methods and datasets are proposed for detecting such data. However, recent research less considers facial animation, which is also important in the forgery attack side. It tries to animate face images with actions provided by driving videos. Our experiments show that the existed datasets a
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17

Svatos, Karl Benton West. "Data-driven, Mediterranean, A.I. simulations and the ethical implications of embedded qualitative bias in digital twin deepfake games." Thesis, Svatos, Karl Benton West ORCID: 0000-0003-1468-0601 (2021) Data-driven, Mediterranean, A.I. simulations and the ethical implications of embedded qualitative bias in digital twin deepfake games. PhD thesis, Murdoch University, 2021. https://researchrepository.murdoch.edu.au/id/eprint/63264/.

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Put simply, the question that has intrigued me and led me to do a PhD is to undertake scientific research which gave me the opportunity to study the underlying ethical and philosophical bases of the research process itself. The thesis takes the reader through real-life studies which combine developing computational power with the handling of large datasets and the ethics of data collection and ownership. This journey resulted in the study and representation of real-life and in-silico or digitalised copies of research data (called digital twins) and compares their physical and in-silico represe
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Trabelsi, Anis. "Robustesse aux attaques en authentification digitale par apprentissage profond." Electronic Thesis or Diss., Sorbonne université, 2022. http://www.theses.fr/2022SORUS580.

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L'identité des personnes sur Internet devient un problème de sécurité majeur. Depuis les accords de Bale, les institutions bancaires ont intégré la vérification de l'identité des personnes ou Know Your Customer (KYC) dans leur processus d'inscription. Avec la dématérialisation des banques, cette procédure est devenue l'e-KYC ou KYC à distance qui fonctionne à distance via le smartphone de l'utilisateur. De même, la vérification d'identité à distance est devenue la norme pour l'inscription aux outils de signature électronique. De nouvelles réglementations émergent pour sécuriser cette approche,
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19

Parascandolo, Fiorenzo. "Trading System: a Deep Reinforcement Learning Approach." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2022.

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The main objective of this work is to show the advantages of Reinforcement Learning-based approaches to develop a Trading System. The experimental results showed the great adaptability of the developed models, which obtained very satisfactory econometric performances in five datasets of Forex Market characterized by different volatilities. The TradingEnv baseline provided by OpenAi was used to simulate the financial market. The latter has been improved by implementing a rendering of the simulation and the commission plan applied by a real Electronic Communication Network. As regards the art
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20

Moufidi, Abderrazzaq. "Machine Learning-Based Multimodal integration for Short Utterance-Based Biometrics Identification and Engagement Detection." Electronic Thesis or Diss., Angers, 2024. http://www.theses.fr/2024ANGE0026.

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Le progrès rapide et la démocratisation de la technologie ont conduit à l’abondance des capteurs. Par conséquent, l’intégration de ces diverses modalités pourrait présenter un avantage considérable pour de nombreuses applications dans la vie réelle, telles que la reconnaissance biométrique ou la détection d’engagement des élèves. Dans le domaine de la multimodalité, les chercheurs ont établi des architectures variées de fusion, allant des approches de fusion précoce, hybride et tardive. Cependant, ces architectures peuvent avoir des limites en ce qui concerne des signaux temporels d’une durée
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21

SONI, ANKIT. "DETECTING DEEPFAKES USING HYBRID CNN-RNN MODEL." Thesis, 2022. http://dspace.dtu.ac.in:8080/jspui/handle/repository/19168.

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We are living in the world of digital media and are connected to various types of digital media contents present in form of images and videos. Our lives are surrounded by digital contents and thus originality of content is very important. In the recent times, there is a huge emergence of deep learning-based tools that are used to create believable manipulated media known as Deepfakes. These are realistic fake media, that can cause threat to reputation, privacy and can even prove to be a serious threat to public security. These can even be used to create political distress, spread f
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22

RASOOL, AALE. "DETECTING DEEPFAKES WITH MULTI-MODEL NEURAL NETWORKS: A TRANSFER LEARNING APPROACH." Thesis, 2023. http://dspace.dtu.ac.in:8080/jspui/handle/repository/19993.

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The prevalence of deepfake technology has led to serious worries about the veracity and dependability of visual media. To reduce any harm brought on by the malicious use of this technology, it is essential to identify deepfakes. By using the Vision Transformer (ViT) model for classification and the InceptionResNetV2 architecture for feature extraction, we offer a novel approach to deepfake detection in this thesis. The highly discriminative features are extracted from the input photos using the InceptionResNetV2 network, which has been pre-trained on a substantial dataset. The Vi
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23

KHICHI, MANISH. "DEEPFAKE OR REAL IMAGE PREDICTION USING MESONET." Thesis, 2021. http://dspace.dtu.ac.in:8080/jspui/handle/repository/18952.

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Advance development in Machine Learning, Deep Learning, and Artificial Intelli gence (AI) allow people to exchange the faces and voices of other people in videos so that they look like people did or wanted to say. These videos and photos are called ”deepfake” and each day they are more complicated, which worries legislators. This technology uses machine learning technology to provide the computer with real data about the image so that we can falsify it. The creators of Deepfake use artificial in telligence and machine learning algorithms to mimic the work and characteristics of the real h
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24

Chang, Ching-Tang, and 張景棠. "Detecting Deepfake Videos with CNN and Image Partitioning." Thesis, 2019. http://ndltd.ncl.edu.tw/cgi-bin/gs32/gsweb.cgi/login?o=dnclcdr&s=id=%22107NCHU5394052%22.&searchmode=basic.

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碩士<br>國立中興大學<br>資訊科學與工程學系所<br>107<br>The AI­generated images are gradually similar to the pictures taken. When the generated images are used in inappropriate cases, it will cause damage to people’s rights and benefits. These doubtful images will cause illegal problems. The issue of detecting digital forgery has existed for many years. However, the fake images generated by the development of science and technology are more difficult to distinguish. Therefore, this thesis based on deep learning technology to detect the controversial face manipulation images. We proposed to segment the image bloc
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Gustav, Lindström, and Lerbom Ludvig. "AI - ett framtida verktyg för terrorism och organiserad brottslighet? : En framtidsstudie." Thesis, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:hh:diva-44890.

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This paper explores the future of Artificial Intelligence (AI) and how it can be used by organised crime orterrorist organisations. It exploresthe fundamentals of AI, its history and how its use is affecting the waypolice operate. The paper shows how the development rate of AI is increasing and predicts how it willcontinue to evolve based on different parameters. A study of different types of AI shows the different usesthese systems have, and their potential misuse in the near future. By using the six pillars approach, aprediction concerning AI and the development of Artificial General Intelli
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