An improved deepfake detection using deep learning
This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science, 2022.
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Brac University
2023
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| Acesso em linha: | http://hdl.handle.net/10361/21834 |
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10361-218342023-10-16T21:04:07Z An improved deepfake detection using deep learning Paul, Annay Dey, Binayak Kumar Mostafa, Md Mosfakin, Maharin Tonika, Rukshana Amin Hossain, Muhammad Iqbal Department of Computer Science and Engineering, Brac University Deepfake GAN CNN Reverse engineering of GM’s RNN Online manipulation--Prevention Deepfakes This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science, 2022. Cataloged from PDF version of thesis. Includes bibliographical references (pages 30-32). With the emergence of Generative Models for creating Deepfake images, and videos of high quality, which are extremely realistic and hard to recognize, several social, and political issues have come to light. DeepFakes of celebrities and political personalities are used to exploit and spread misinformation that leads to several social and political unrest. Hence, the necessity to develop a methodology to detect such images and videos created with DeepFakes has arisen in recent times. Several state- of-the-art methodologies are in use for the purpose such as CNN, RNN, reverse engineering of GMs, neural networks, ensemble-based learning approaches, etc. As many machine learning-based approaches are already adopted, our aim is to improve the quality of detection of DeepFakes using models that utilize deep learning, in our study. The state-of-the-art methodologies have shown promising results when ap- plied to popular datasets vastly used for training and research purposes. However, most methods are not robust enough to perform well in all kinds of general-purpose DeepFakes. Hence, in this paper, we have developed a new comprehensive and ef- ficient framework that improves the DeepFake detection performance not only on general purpose but also on training purpose data. Annay Paul Binayak Kumar Dey Md Mostafa Maharin Mosfakin Rukshana Amin Tonika B.Sc. in Computer Science 2023-10-16T04:53:30Z 2023-10-16T04:53:30Z ©2022 2022-09-28 Thesis ID 18301097 ID 18301054 ID 18301132 ID 18301119 ID 18301247 http://hdl.handle.net/10361/21834 en Brac University theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. 42 pages application/pdf Brac University |
| institution |
Brac University |
| collection |
Institutional Repository |
| language |
English |
| topic |
Deepfake GAN CNN Reverse engineering of GM’s RNN Online manipulation--Prevention Deepfakes |
| spellingShingle |
Deepfake GAN CNN Reverse engineering of GM’s RNN Online manipulation--Prevention Deepfakes Paul, Annay Dey, Binayak Kumar Mostafa, Md Mosfakin, Maharin Tonika, Rukshana Amin An improved deepfake detection using deep learning |
| description |
This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science, 2022. |
| author2 |
Hossain, Muhammad Iqbal |
| author_facet |
Hossain, Muhammad Iqbal Paul, Annay Dey, Binayak Kumar Mostafa, Md Mosfakin, Maharin Tonika, Rukshana Amin |
| format |
Thesis |
| author |
Paul, Annay Dey, Binayak Kumar Mostafa, Md Mosfakin, Maharin Tonika, Rukshana Amin |
| author_sort |
Paul, Annay |
| title |
An improved deepfake detection using deep learning |
| title_short |
An improved deepfake detection using deep learning |
| title_full |
An improved deepfake detection using deep learning |
| title_fullStr |
An improved deepfake detection using deep learning |
| title_full_unstemmed |
An improved deepfake detection using deep learning |
| title_sort |
improved deepfake detection using deep learning |
| publisher |
Brac University |
| publishDate |
2023 |
| url |
http://hdl.handle.net/10361/21834 |
| work_keys_str_mv |
AT paulannay animproveddeepfakedetectionusingdeeplearning AT deybinayakkumar animproveddeepfakedetectionusingdeeplearning AT mostafamd animproveddeepfakedetectionusingdeeplearning AT mosfakinmaharin animproveddeepfakedetectionusingdeeplearning AT tonikarukshanaamin animproveddeepfakedetectionusingdeeplearning AT paulannay improveddeepfakedetectionusingdeeplearning AT deybinayakkumar improveddeepfakedetectionusingdeeplearning AT mostafamd improveddeepfakedetectionusingdeeplearning AT mosfakinmaharin improveddeepfakedetectionusingdeeplearning AT tonikarukshanaamin improveddeepfakedetectionusingdeeplearning |
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1814307294207279104 |