Creating machine learning models for detecting the application of specific deepfake tools

A system for training a detection machine learning model (ML) for identifying a specific deepfake tool of a plurality of deepfake tools used to create a deepfake video, comprising:

• at least one processor executing a code for:
• feeding a plurality of sample authentic videos into the specific deepfake tool;
• obtaining a plurality of deepfake videos as an outcome of the specific deepfake tool;
• creating a training dataset comprising a plurality of records, wherein a record includes a deepfake video labelled with a ground truth indicating the specific deepfake tool used to create the deepfake video;
• training the detection ML model on the training dataset for detecting that the specific deepfake tool was used to create an input deepfake video;
• creating a second plurality of records for inclusion in the training dataset for balancing the training dataset, the second plurality of records including a second plurality of sample authentic videos corresponding to the class, labelled with a ground truth indicating lack of use of the specific deepfake tool;
• identifying a class of the specific deepfake tool according to at least one adaptation performed by the specific deepfake tool on an input video;
• and
• selecting the plurality of sample authentic videos corresponding to the class,
• wherein the plurality of deepfake videos are modified by the specific deepfake tool based on the class.

A non-transitory medium storing program instructions for training a detection ML model for identifying a specific deepfake tool of a plurality of deepfake tools used to create a deepfake video, which when executed by at least one processor, cause the at least one processor to:

• feed a plurality of sample authentic videos into the specific deepfake tool;
• obtain a plurality of deepfake videos as an outcome of the specific deepfake tool;
• create a training dataset comprising a plurality of records, wherein a record includes a deepfake video labelled with a ground truth indicating the specific deepfake tool used to create the deepfake video;
• train the detection ML model on the training dataset for detecting that the specific deepfake tool was used to create an input deepfake video create a second plurality of records for inclusion in the training dataset for balancing the training dataset, the second plurality of records including a second plurality of sample authentic videos corresponding to the class, labelled with a ground truth indicating lack of use of the specific deepfake tool;
• identify a class of the specific deepfake tool according to at least one adaptation performed by the specific deepfake tool on an input video;
• and
• select the plurality of sample authentic videos corresponding to the class,
• wherein the plurality of deepfake videos are modified by the specific deepfake tool based on the class.