A method, system, storage medium, and terminal for generating adversarial examples

Abstract

This invention discloses an adversarial example generation method, system, storage medium, and terminal, belonging to the field of adversarial attack technology. The method includes: determining the context region of a target object and dividing it into multiple sub-regions; performing importance analysis on each sub-region; mapping the influence of each sub-region on the detection results of the target detection model to the context region, generating a context attribution graph; selecting one or more influential sub-regions exceeding an influence threshold; and fine-tuning the influential sub-regions under a total loss function (including a loss function and a perceptual loss function) to generate adversarial examples. This invention accurately guides the attack direction through the context attribution graph and introduces a dual loss function, suppressing position, direction, and confidence prediction while ensuring the visual imperceptibility of adversarial perturbations, thus preserving the integrity of the target object and enhancing the stealth of the attack. Attacking only some influential sub-regions improves attack efficiency.

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