Özet
Deep learning is widely used to create artificial contents on the Internet. Similarly, it is also used to detect fake contents. Fake frames created and integrated with deep learning algorithms are known as deepfake. Recently, malicious users tend to use deepfake to manipulate genuine contents to carry out variety of attacks. Video conferencing apphcations has been a significant target of the malicious users since the beginning of Covid-19 pandemic who use deepfake models to create fake virtual identities in onhne video conferences. We propose a lightweight deepfake detection model that may be integrated with video conference applications to detect fake faces. Experimental analyses show that the proposed model provides acceptable accuracy to detect fake images on video conferences.
| Orijinal dil | İngilizce |
|---|---|
| Ana bilgisayar yayını başlığı | Proceedings - 6th International Conference on Computer Science and Engineering, UBMK 2021 |
| Yayınlayan | Institute of Electrical and Electronics Engineers Inc. |
| Sayfalar | 36-41 |
| Sayfa sayısı | 6 |
| ISBN (Elektronik) | 9781665429085 |
| DOI'lar | |
| Yayın durumu | Yayınlandı - 2021 |
| Etkinlik | 6th International Conference on Computer Science and Engineering, UBMK 2021 - Ankara, Türkiye Süre: 15 Eyl 2021 → 17 Eyl 2021 |
Yayın serisi
| Adı | Proceedings - 6th International Conference on Computer Science and Engineering, UBMK 2021 |
|---|
???event.eventtypes.event.conference???
| ???event.eventtypes.event.conference??? | 6th International Conference on Computer Science and Engineering, UBMK 2021 |
|---|---|
| Ülke/Bölge | Türkiye |
| Şehir | Ankara |
| Periyot | 15/09/21 → 17/09/21 |
Bibliyografik not
Publisher Copyright:© 2021 IEEE
Parmak izi
Deepfake and Security of Video Conferences' araştırma başlıklarına git. Birlikte benzersiz bir parmak izi oluştururlar.Alıntı Yap
- APA
- Author
- BIBTEX
- Harvard
- Standard
- RIS
- Vancouver