A method for verifying an integrity of one or more parameters of a neural network by inserting a test pattern into a background area of an input image, the method comprising the steps of: (a) a computing device , acquiring each of a (t-2)-th image and a (t-1)-th image respectively corresponding to (t-i2)-th frame and (t-i1)-th frame of a video, wherein each of i2 and i1 is an arbitrary integer, and i2 is larger than i1, and instructing a background prediction unit to generate t-th background prediction information of a t-th image by referring to the information on said each of the (t-2)-th image and the (t-1)-th image; (b) the computing device , acquiring the t-th image, and instructing a pattern insertion unit to insert the test pattern into a background area of the t-th image by referring to the t-th background prediction information, to thereby generate an input for verification; (c) the computing device instructing the neural network to generate an output for verification by applying one or more convolution operations to the input for verification; and (d) the computing device instructing a verification unit to determine the integrity of the neural network by referring to the output for verification and an output for reference corresponding to the test pattern, wherein the output for reference was generated by the neural network by applying the convolution operations to the test pattern when a security level of the computing device was higher than a threshold level, and wherein, at the step of (d), the computing device instructs the verification unit to compare values included in the output for reference and values included in a specific area, corresponding to the test pattern, among a whole area of the output for verification, and, if at least one of the values included in the specific area is different from its corresponding value included in the output for reference, the computing device instructs the verification unit to determine that at least part of one or more parameters of the neural network has been changed. (a) a computing device , acquiring each of a (t-2)-th image and a (t-1)-th image respectively corresponding to (t-i2)-th frame and (t-i1)-th frame of a video, wherein each of i2 and i1 is an arbitrary integer, and i2 is larger than i1, and instructing a background prediction unit to generate t-th background prediction information of a t-th image by referring to the information on said each of the (t-2)-th image and the (t-1)-th image; (b) the computing device , acquiring the t-th image, and instructing a pattern insertion unit to insert the test pattern into a background area of the t-th image by referring to the t-th background prediction information, to thereby generate an input for verification; (c) the computing device instructing the neural network to generate an output for verification by applying one or more convolution operations to the input for verification; and (d) the computing device instructing a verification unit to determine the integrity of the neural network by referring to the output for verification and an output for reference corresponding to the test pattern, wherein the output for reference was generated by the neural network by applying the convolution operations to the test pattern when a security level of the computing device was higher than a threshold level, and <EOS>