Abstract:
An apparatus and method for storing device data in an IoT environment. An apparatus for providing a data storage function includes an authentication unit for performing device authentication with a data storage-requesting device and performing data storage authentication with the data storage-requesting device, a data storage unit for storing encryption key basis information, used to generate an encryption key for data encryption, and encrypted data, a request message processing unit for processing a processing request message for the encrypted data received from the data storage-requesting device using the data storage unit, and a communication unit for receiving the processing request message from the data storage-requesting device and transmitting results of processing to the data storage-requesting device.
Abstract:
Disclosed herein are a user terminal and method for playing DRM content. The user terminal includes a common security platform. The common security platform includes a DRM application management unit and a security management unit. The DRM application management unit stores and executes a DRM application that requests authentication from a license server and receives a license, including a decryption key for decrypting encrypted DRM content. The DRM application is an application in a downloadable form. The security management unit decrypts the encrypted DRM content, provided by a content providing server, using the decryption key included in the license issued via the DRM application.
Abstract:
Disclosed herein is a method for measuring the weight of a discrete entity, performed in a neural network model configured with multiple layers, the method including receiving data configured with the indices of discrete entities, converting the data into embedding vectors corresponding to respective indices through an embedding layer, generating a masked vector through element-wise multiplication between a mask vector and the embedding vector, calculating a loss using output based on the masked vector, and training the model based on the loss.
Abstract:
Disclosed herein are an apparatus and method for detecting a malicious device based on swarm intelligence. The method includes detecting a malicious device by causing at least one exploration ant to access a device swarm along movement routes in which pheromone trail values are taken into consideration, wherein the exploration ant is generated in response to a detection request received from a security management server, when the at least one exploration ant detects a suspicious device that is suspected to be a malicious device, causing the exploration ant to return along the movement routes in reverse order, and returning pheromone trail values generated by devices on the return movement routes to a malicious device detection apparatus, and identifying whether the suspicious device is the malicious device by calculating an optimal solution based on a local information set generated by aggregating the pheromone trail values returned for movement routes.
Abstract:
Disclosed herein are a fixed-location Internet-of-Things (IoT) device for protecting secure storage access information and a method for protecting secure storage access information of the fixed-location IoT device. The fixed-location IoT device includes a unique hardware information analysis unit for generating a hardware hash value by analyzing unique hardware information corresponding to the fixed-location IoT device for protecting the secure storage access information, a network environment information collection unit for collecting network environment information from neighboring fixed-location IoT devices, a network environment information analysis unit for generating a network hash value by analyzing the network environment information, an access information encryption key generation unit for generating an access information encryption key corresponding to the secure storage access information using the hardware hash value and the network hash value, and an encryption/decryption unit for encrypting or decrypting the secure storage access information using the access information encryption key.
Abstract:
Disclosed herein are a device and method for updating firmware and a firmware update system. The device for updating firmware include an update manager for receiving delta information about the latest version of firmware from an update server by checking information about a version of firmware installed in a terminal device and for updating the firmware installed in the terminal device using the delta information, and a bootloader for restoring the updated firmware using previously stored backup information when the updated firmware is not normally launched or when an error occurs during the update of the firmware.
Abstract:
Disclosed herein is an electronic device including a message creation unit for creating an authentication message that includes hardware information and security level information for mutual authentication with an additional electronic device; a communication unit for sending the authentication message to the additional electronic device and receiving an authentication message of the additional electronic device from the additional electronic device; an authentication algorithm selection unit for selecting an authentication algorithm for mutual authentication with the additional electronic device based on hardware information and security level information of the additional electronic device, which are included in the authentication message of the additional electronic device; and an authentication processing unit for performing a mutual authentication process using the selected authentication algorithm.
Abstract:
There is provided a method of fault management of a smart device including comparing a value of a fault detection indicator (hereinafter referred to as ‘FDI’) in a normal state, which detects faults generated in the smart device, with respect to at least one performance indicator, with an FDI value observed in real time and detecting the faults by calculating a relative variation level of the observed values, and creating a diagnosis object (hereinafter referred to as ‘DO’) including a cause and a countermeasure of the detected fault and analyzing the fault.