用相机取证技术识别自拍银行中的深度伪造图像
Addressing Deepfake Issue in Selfie banking through camera based authentication
- 利用相机特征分析自拍图像来源，检测伪造痕迹
- 可识别深度学习生成的高仿真假脸，准确率显著提升
- 适合金融安全团队和反欺诈系统开发者参考
自拍银行中的虚假图像正日益构成威胁。过去仅靠Photoshop伪造，如今深度学习技术能生成高度逼真的假身份，被犯罪分子用于绕过人脸识别等生物认证系统。本文探索了一种已有的图像相机定位取证技术在深度伪造检测中的应用，通过分析自拍图像的相机特征，识别由深度学习生成的伪造痕迹，为在线银行安全提供新的防御手段。
原文摘要 · Abstract (English)
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.
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