Abstract: An electronic device is disclosed. The electronic device comprises: a communication interface; a memory in which a learning network model for predicting next data by learning temporally continuous data is stored; and a processor for acquiring prediction data that is to replace data received from the learning network model, when the occurrence of an error in data received from a sensor device through the communication interface is identified, performing an autonomous driving function on the basis of the acquired prediction data, counting the number of error occurrences, and providing information informing that a sensing state of the sensor device is abnormal, when the counting frequency is greater than or equal to a threshold value.

Abstract: An electronic device is disclosed. The electronic device comprises a communication interface, a memory in which a program for performing an autonomous driving function is stored, and a processor which performs second processing for first processed data on the basis of a first program stored in the memory, when the first processed data is received from an external sensor device through the communication interface, and which performs, on the basis of a second program stored in the memory, first processing for raw data received from the external sensor device, and then performs the second processing on the basis of the first program, when the occurrence of an error in the reception of the data is identified.

Abstract: An electronic apparatus and a method for controlling thereof are provided. The electronic apparatus includes a memory storing an artificial neural network and metadata including information of at least one layer in the artificial neural network, and a processor configured to: acquire a security vector based on the metadata and a security key of the electronic apparatus; map the security vector and the metadata with the security key and identification information of the artificial neural network; perform encryption on the at least one layer based on the metadata and the security vector; based on input data input to the artificial neural network, load the metadata and the security vector by using the security key and the identification information of the artificial neural network; and perform an operation between the input data and the encrypted at least one layer based on the loaded security vector and the metadata.

Abstract: An electronic device is disclosed. The electronic device comprises a communication interface, a memory in which a program for performing an autonomous driving function is stored, and a processor which performs second processing for first processed data on the basis of a first program stored in the memory, when the first processed data is received from an external sensor device through the communication interface, and which performs, on the basis of a second program stored in the memory, first processing for raw data received from the external sensor device, and then performs the second processing on the basis of the first program, when the occurrence of an error in the reception of the data is identified.

Abstract: An electronic device is disclosed. The electronic device comprises: a communication interface; a memory in which a learning network model for predicting next data by learning temporally continuous data is stored; and a processor for acquiring prediction data that is to replace data received from the learning network model, when the occurrence of an error in data received from a sensor device through the communication interface is identified, performing an autonomous driving function on the basis of the acquired prediction data, counting the number of error occurrences, and providing information informing that a sensing state of the sensor device is abnormal, when the counting frequency is greater than or equal to a threshold value.