Abstract: A method for concealing original data to protect personal information is provided. The method includes steps of: a data obfuscation device (a) if the original data is acquired, inputting the original data or its modified data into a learning network, and allowing the learning network to (i) apply a network operation to the original data or the modified data using learned parameters of the learning network and thus to (ii) output characteristic information on the original data or the modified data; and (b) updating the original data or the modified data via backpropagation using part of (i) 1-st losses calculated by referring to the characteristic information and its corresponding 1-st ground truth, and (ii) 2-nd losses calculated by referring to (ii-1) a task specific output generated by using the characteristic information (ii-2) a 2-nd ground truth corresponding to the task specific output, to thereby generate obfuscated data.

Abstract: A method for concealing original data to protect personal information is provided. The method includes steps of: a data obfuscation device (a) if the original data is acquired, inputting the original data or its modified data into a learning network, and allowing the learning network to (i) apply a network operation to the original data or the modified data using learned parameters of the learning network and thus to (ii) output characteristic information on the original data or the modified data; and (b) updating the original data or the modified data via backpropagation using part of (i) 1-st losses calculated by referring to the characteristic information and its corresponding 1-st ground truth, and (ii) 2-nd losses calculated by referring to (ii-1) a task specific output generated by using the characteristic information and (ii-2) a 2-nd ground truth corresponding to the task specific output, to thereby generate obfuscated data.

Abstract: A method for learning an obfuscation network used for concealing original data is provided. The method includes steps of: a learning device instructing the obfuscation network to obfuscate inputted training data, inputting the obfuscated training data into a learning network, and allowing the learning network to apply a network operation to the obfuscated training data and thus to generate 1-st characteristic information, and allowing the learning network to apply a network operation to the inputted training data and thus to generate 2-nd characteristic information, and learning the obfuscation network such that an error is minimized, calculated by referring to part of an error acquired by referring to the 1-st and the 2-nd characteristic information, and an error acquired by referring to a task specific output and its corresponding ground truth, and such that an error is maximized, calculated by referring to the training data and the obfuscated training data.

Abstract: A method for learning an adaption network corresponding to an obfuscation network used for concealing original data is provided. The method includes steps of: (a) on condition that a 1-st learning device has performed or is performing processes of (i) instructing the obfuscation network to obfuscate the training data to generate obfuscated training data, (ii) inputting the obfuscated training data into a learning network to generate 1-st characteristic information for training and inputting the training data into the learning network to generate 2-nd characteristic information for training, and (iii) learning the obfuscation network, a 2-nd learning device performing one of inputting the training data into the adaption network to generate 1-st feature adapted data and inputting test data into the adaption network to generate 2-nd feature adapted data and one of (i) acquiring a 1-st adaption ground truth and learning the adaption network and (ii) learning the adaption network.

Abstract: A method for learning a user learning network to recognize obfuscated data created by concealing original data is provided. The method includes steps of: a 2-nd learning device, (a) on condition that a 1-st learning device has performed (i) instructing the obfuscation network to generate obfuscated training data, (ii) inputting (ii-1) the obfuscated training data into, to generate 1-st characteristic information for training, and (ii-2) the training data, to generate 2-nd characteristic information for training, into a learning network for training and (iii) learning the obfuscation network, and acquiring (i) the obfuscated training data and a training data GT, or (ii) obfuscated test data and a test data GT; (b) inputting (i) the obfuscated training data, to generate 3-rd characteristic information for training, or (ii) the obfuscated test data, to generate 4-th characteristic information for training, into the user learning network; and (c) learning the user learning network.

Abstract: A method for learning a data embedding network is provided. The method includes steps of: a learning device acquiring and inputting original training data and mark training data into the data embedding network which integrates them and generates marked training data; inputting the marked training data into a learning network which applies a network operation to them and generates 1-st characteristic information, and inputting the original training data into the learning network which applies a network operation to them and generates 2-nd characteristic information; learning the data embedding network such that a data error is minimized, by referring to part of errors referring to the 1-st and the 2-nd characteristic information and errors referring to task specific outputs and their ground truths, and a marked data score is maximized, and learning a discriminator such that a original data score is maximized and the marked data score is minimized.

Abstract: A method for concealing original data to protect personal information is provided. The method includes steps of: a data obfuscation device (a) if the original data is acquired, inputting the original data or its modified data into a learning network, and allowing the learning network to (i) apply a network operation to the original data or the modified data using learned parameters of the learning network and thus to (ii) output characteristic information on the original data or the modified data; and (b) updating the original data or the modified data via backpropagation using part of (i) 1-st losses calculated by referring to the characteristic information and its corresponding 1-st ground truth, and (ii) 2-nd losses calculated by referring to (ii-1) a task specific output generated by using the characteristic information (ii-2) a 2-nd ground truth corresponding to the task specific output, to thereby generate obfuscated data.

Abstract: A method for learning an obfuscation network used for concealing original data is provided. The method includes steps of: a learning device instructing the obfuscation network to obfuscate inputted training data, inputting the obfuscated training data into a learning network, and allowing the learning network to apply a network operation to the obfuscated training data and thus to generate 1-st characteristic information, and and allowing the learning network to apply a network operation to the inputted training data and thus to generate 2-nd characteristic information, and learning the obfuscation network such that an error is minimized, calculated by referring to part of an error acquired by referring to the 1-st and the 2-nd characteristic information, and an error acquired by referring to a task specific output and its corresponding ground truth, and such that an error is maximized, calculated by referring to the training data and the obfuscated training data.