| CPC G06V 10/82 (2022.01) [G06F 18/2148 (2023.01); G06F 18/217 (2023.01); G06F 18/285 (2023.01); G06N 5/04 (2013.01); G06N 20/00 (2019.01); G06V 20/30 (2022.01); G06V 20/41 (2022.01)] | 20 Claims |
|
1. An apparatus comprising:
one or more processors to:
store a plurality of deepfake detection models corresponding to a plurality of subjects of interest, wherein the plurality of deepfake detection models are each generated using subject-specific data collected for a corresponding subject of interest of the plurality of subjects of interest and the plurality of deepfake detection models are trained using the subject-specific data to distinguish synthetic data from authentic data corresponding to the plurality of subjects of interest;
receive a query to identify whether data pertaining to a target subject of interest is a deepfake, the target subject of interest comprised in the plurality of subjects of interest and associated with a subject identifier (ID);
identify, using the subject ID, a deepfake detection model corresponding to the subject ID from the plurality of deepfake detection models;
extract features for deepfake detection from the data pertaining to the target subject of interest, wherein the features comprise a combination of face, voice, and text corresponding to the target subject of interest;
input the features to the deepfake detection model corresponding to the subject ID; and
responsive to an output of the deepfake detection model satisfying a determined deepfake threshold, generate a notification, in response to the query, indicating a possible deepfake attack corresponding to the target subject of interest;
wherein the plurality of deepfake detection models are stored on a local computing device and trained at the local computing device based on training features extracted from communication data with the plurality of subjects of interest at the local computing device and based on synthetic deepfake data of the plurality of subjects of interest created at the local computing device.
|