Addressing Deepfake Issue in Selfie banking through camera based authentication

TL;DR

This paper investigates using a forensic recognition system, originally designed for camera localization, to detect deepfake images in selfie banking, aiming to enhance biometric security against increasingly realistic fake identities.

Contribution

It introduces a novel application of an existing forensic recognition system for deepfake detection in selfie banking, addressing a critical security challenge.

Findings

Effective detection of deepfakes in selfie banking images

Potential integration with biometric authentication systems

Improved security against deepfake-based fraud

Abstract

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.