METHOD FOR WATERMARKING A MACHINE LEARNING MODEL

A method is provided for watermarking a machine learning model used for object detection or image classification. In the method, a first subset of a labeled set of ML training samples is selected. The first subset is of a predetermined class of images. In one embodiment, the first pixel pattern is selected and sized to have substantially the same dimensions as each sample of the first subset or each bounding box in the case of an object detector. Each sample of the first subset is relabeled to have a different label than the original label. An opacity of the pixel pattern may be adjusted independently for different parts of the pattern. The ML model is trained with the labeled set of ML training samples and the first subset of relabeled ML training samples. Using multiple different opacity factors provides both reliability and credibility to the watermark.