Addressing Deepfake Issue in Selfie banking through camera based authentication
Fuente:
arXiv
Saved in:
| Main Authors: | , |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1866916920931909632 |
|---|---|
| author | Mukherjee, Subhrojyoti Mohanty, Manoranjan |
| author_facet | Mukherjee, Subhrojyoti Mohanty, Manoranjan |
| contents | Fake images in selfie banking are increasingly becoming a threat. Previously, it was just Photoshop, but now deep learning technologies enable us to create highly realistic fake identities, which fraudsters exploit to bypass biometric systems such as facial recognition in online banking. This paper explores the use of an already established forensic recognition system, previously used for picture camera localization, in deepfake detection. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2508_19714 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Addressing Deepfake Issue in Selfie banking through camera based authentication Mukherjee, Subhrojyoti Mohanty, Manoranjan Cryptography and Security Computer Vision and Pattern Recognition Fake images in selfie banking are increasingly becoming a threat. Previously, it was just Photoshop, but now deep learning technologies enable us to create highly realistic fake identities, which fraudsters exploit to bypass biometric systems such as facial recognition in online banking. This paper explores the use of an already established forensic recognition system, previously used for picture camera localization, in deepfake detection. |
| title | Addressing Deepfake Issue in Selfie banking through camera based authentication |
| topic | Cryptography and Security Computer Vision and Pattern Recognition |
| url | https://arxiv.org/abs/2508.19714 |