Potential Threat of Face Swapping to eKYC with Face Registration and Augmented Solution with Deepfake Detection.

It is necessary to develop an efficient and secure mechanism to verify customers digitally for various online transactions. Integrating biometric solutions into the online user registration and verification processes is a promising trend for electronic Know Your Customer (eKYC) systems. However, Deepfake or face manipulation techniques may become a threat for eKYC with face authentication. In this paper, we introduce this potential attack of Deepfake on eKYC by swapping and manipulating faces between source and target faces. We then propose to augment the security for current eKYC systems with Deepfake detection. We conduct the experiments on the 10K video clips in the private test of Deepfake Detection Challenge 2020, and our method, following the Capsule-forensics approach, achieves the Logloss score of 0.5189, among the top 6% best results among the 2114 teams worldwide. This result demonstrates that our deepfake detection algorithm can be a promising method to provide extra protection for eKYC solutions with face registration and authentication.