The invention discloses a non-directional white-box attack resisting method for scene character recognition, which is characterized in that noise which is difficult to perceive by human eyes is added into an input image, so that a character recognition algorithm obtains a recognition result which is totally different from the original recognition result, and the effect of attacking a scene character recognition network model is achieved. Different from common object recognition, a character recognition result is a character sequence, so that an existing adversarial attack method cannot be directly applied to scene character recognition. Therefore, the method comprises the following steps: firstly, an objective function in a single object classification adversarial attack algorithm is modified into a sequence form; in order to accelerate generation of an adversarial sample, a step function is introduced in, and once a character is different from the recognition result of the original image in the recognition result of the adversarial sample, the penalty of the target function is zero; besides, in consideration of different attack difficulty levels of different samples, the more easily recognized correctly the samples are, the more difficultly attacked the samples are, recognition scores are introduced into the target function, so that adversarial samples with smaller disturbance are obtained.