Abstract: In accordance with an aspect of the present disclosure, there is provided an adversarial self-supervised learning method for an encoder. The method comprises selecting a target image of an original image for training from an image group included in a previously collected dataset; generating a noise image by combining the original image for training with noise using the original image for training and the target image; and training the encoder using the noise image and the original image for training.

Abstract: In accordance with an aspect of the present disclosure, there is provided an adversarial self-supervised learning method for an encoder. The method comprises selecting a target image of an original image for training from an image group included in a previously collected dataset; generating a noise image by combining the original image for training with noise using the original image for training and the target image; and training the encoder using the noise image and the original image for training.

Abstract: Disclosed is a random sampling-based collective classification method and system for Sybil account detection. A random sampling-based collective classification method performed by a collective classification system may include performing a first collective classification using training data; constructing sampled new training data by randomly extracting a portion of the entire nodes based on a label assigned to each node according to a result of performing the first collective classification; performing a second collective classification using the constructed new training data; and applying a posterior score difference of each node computed through the first collective classification and the second collective classification to a prior score of each node to be used for training data at a next iteration.

Abstract: The present disclosure in at least one embodiment provides a method of providing an advertisement disclosure for advertisement identification to a content that is displayed in a three-dimensional space by a visual interface, including detecting an advertisement object located within a user sight from the content, inserting the advertisement disclosure in an adjacent position to the advertisement object, and controlling the advertisement disclosure in position or orientation based on a user gaze upon detecting the user gaze.

Abstract: The present disclosure in at least one embodiment provides a method of providing an advertisement disclosure for advertisement identification to a content that is displayed in a three-dimensional space by a visual interface, including detecting an advertisement object located within a user sight from the content, inserting the advertisement disclosure in an adjacent position to the advertisement object, and controlling the advertisement disclosure in position or orientation based on a user gaze upon detecting the user gaze.

Abstract: Disclosed is a method of evaluating robustness of artificial neural network watermarking against model stealing attacks. The method of evaluating robustness of artificial neural network watermarking may include the steps of: training an artificial neural network model using training data and additional information for watermarking; collecting new training data for training a copy model of a structure the same as that of the trained artificial neural network model; training the copy model of the same structure by inputting the collected new training data into the copy model; and evaluating robustness of watermarking for the trained artificial neural network model through a model stealing attack executed on the trained copy model.

Abstract: Disclosed are an apparatus and method for diagnosing an abnormality of a mobile communication network. The apparatus for diagnosing an abnormality of a mobile communication network includes a modeling unit that models a control plane operation of an analysis target mobile communication network based on a control plane messages collected by a preset Mobile Network Operator to a terminal in a formal model of a form of a state machine, an analysis unit that compares processing required times of a control plane operation model of the modeled analysis target mobile communication network and a control plane operation model of another mobile communication network previously generated in a same path, and a detection unit that detects an abnormal operation of the mobile communication network of the analysis target based on a comparison result.

Abstract: Disclosed are an apparatus and method for diagnosing an abnormality of a mobile communication network. The apparatus for diagnosing an abnormality of a mobile communication network includes a modeling unit that models a control plane operation of an analysis target mobile communication network based on a control plane messages collected by a preset Mobile Network Operator to a terminal in a formal model of a form of a state machine, an analysis unit that compares processing required times of a control plane operation model of the modeled analysis target mobile communication network and a control plane operation model of another mobile communication network previously generated in a same path, and a detection unit that detects an abnormal operation of the mobile communication network of the analysis target based on a comparison result.