Images can be regenerated from quantized biometric match score data

We address the possibility of regenerating sample images from stored biometric data, specifically from automatic face recognition algorithms. Such algorithms calculate a match score from comparison of a newly acquired image of a person to a template calculated from previously captured images. Although several vendors of biometric algorithms claim that an image of a person cannot be regenerated from the template, it has been shown that, in general, such regeneration can be performed with a "hill climbing attack". In order to defend against this attack, it is recommended that biometric algorithms emit only quantized match scores. In this paper, we show that it is still possible to regenerate biometric images even if this recommendation is implemented. Each iteration of the algorithm is applied to a quadrant of the sample image. Before each calculation, noise is added to the image in the opposite quadrant, in order to force the match score to a value just below the quantization threshold, providing useful information. Results show this algorithm successfully regenerates images which compare at high match scores for reasonable values of the quantization level. We conclude that the quantization of match score values does not, by itself, protect against the regeneration of images from stored biometric data.