Abstract: Disclosed herein are an artificial Intelligence (AI)-based cyber training method. The AI-based cyber training method may include generating a unit attack by training an attack agent based on environment and state information of a cyber range (CR) and a set of attack tools executable on a system, executing the unit attack in the CR, and then determining whether the unit attack has succeeded, and determining whether to perform an attack or a defense based on whether the unit attack has succeeded.

Abstract: A method of calculating a comprehensive disease index (CDI) is disclosed. The method includes analyzing pieces of medical data to calculate a disease risk value, analyzing pieces of vital data and vital data mapped to standard clinic guideline data among the pieces of vital data to calculate a disease severity value, and analyzing the disease risk value, the disease severity value, and medical knowledge information obtained from a medical knowledge base to calculate the CDI.

Abstract: The present invention relates to a device and method of predicting disease by using elderly cohort data, and more particularly, to a device and method of predicting disease by using elderly cohort data and an elderly disease prediction model applied thereto, which may predict an outbreak possibility of an elderly disease including cerebral stroke by using cohort data of 60 or more-year-old persons.

Abstract: Provided are a data processing apparatus and method for merging and processing deterministic knowledge and non-deterministic knowledge. The data processing apparatus and method may efficiently process various real-time and large-scale data to convert the data into knowledge by merging and processing non-deterministic knowledge and also deterministic knowledge perceived by an expert. Thus, it is possible to adaptively operate in accordance with a dynamically changing application service environment by converting a conversion rule for converting collected data generated from an application service system into semantic data, a context awareness rule for perceiving context information from given information, and a user query for searching for knowledge information into knowledge and gradually augmenting the knowledge information in accordance with an application service environment.

Abstract: Methods and systems for analyzing data. The data analysis method includes generating a case data set corresponding to the data analysis request; collecting and storing raw data corresponding to the case data set; generating a knowledge package based on the raw data; generating a knowledge package library based on the knowledge package; and providing the user with the knowledge package library. Also, the case data set includes first selection parameters, and the knowledge package library includes second selection parameters different from the first selection parameters. According to the embodiments of the present disclosure, a deep understanding of business and ecosystem which is previously obtained from big data analysis and insights about data group selection, modeling, and analysis method can be provided, such that a big data analysis can be performed with enhanced efficiency.

Abstract: Provided are a self-learning system and method for automatically performing machine learning (ML). The self-learning system includes a memory configured to store an ML knowledge database (DB) in which ML knowledge is stored and a program for automatically performing ML based on request information of a user, and a processor configured to execute the program stored in the memory. Here, when executing the program, the processor creates or recommends at least one workflow corresponding to the request information of the user based on the ML knowledge stored in the ML knowledge DB and generates an execution code for performing the created or recommended workflow.

Abstract: Provided is a data meta-scaling method. The data meta-scaling method optimizes an abbreviation criterion for abbreviating data through continuous knowledge augmentation in various dimensions which enable expression of data in a process of performing machine learning.

Abstract: Provided are a data processing apparatus and method for merging and processing deterministic knowledge and non-deterministic knowledge. The data processing apparatus and method may efficiently process various real-time and large-scale data to convert the data into knowledge by merging and processing non-deterministic knowledge and also deterministic knowledge perceived by an expert. Thus, it is possible to adaptively operate in accordance with a dynamically changing application service environment by converting a conversion rule for converting collected data generated from an application service system into semantic data, a context awareness rule for perceiving context information from given information, and a user query for searching for knowledge information into knowledge and gradually augmenting the knowledge information in accordance with an application service environment.

Abstract: Methods and systems for analyzing data. The data analysis method includes generating a case data set corresponding to the data analysis request; collecting and storing raw data corresponding to the case data set; generating a knowledge package based on the raw data; generating a knowledge package library based on the knowledge package; and providing the user with the knowledge package library. Also, the case data set includes first selection parameters, and the knowledge package library includes second selection parameters different from the first selection parameters. According to the embodiments of the present disclosure, a deep understanding of business and ecosystem which is previously obtained from big data analysis and insights about data group selection, modeling, and analysis method can be provided, such that a big data analysis can be performed with enhanced efficiency.

Abstract: There is provided a system for providing information. The system includes a data classifying device configured to receive original data and classify the original data as real time data or general data; a real time data analyzing device configured to receive the real time data from the data classifying device and generate condensed information including only a part that satisfies predefined conditions among attribute information of the real time data; and a distributed parallel processing device configured to receive the general data from the data classifying device, perform a predetermined distributed parallel computation process on the general data, and generate analysis information.

Abstract: Provided is an apparatus and method for detecting a traffic flooding attack and conducting an in-depth analysis using data mining that may rapidly detect a distributed denial of service (DDoS) attack, for example, a traffic flooding attack, developed more variously and firmly from a denial of service (DoS) attack, perform an attack type classification, and conduct a semantic analysis with respect to the attack. The apparatus and method may support a system operation and provide a more stable service, by rapidly detecting a traffic flooding attack, classifying a type of the attack, and conducting a semantic analysis based on a prediction and analysis scheme of data mining.

Abstract: A virtual sensor generation apparatus of a sensor network sets a communication connection to a sensor node at a periphery of a smart device, generates a logical sensor corresponding to a physical sensor that is connected to the sensor node, generates a virtual sensor with the logical sensor, and provides an application service to a user using the virtual sensor.

Abstract: Exemplary embodiments of the present invention relates to a resource sharing for M2M service capabilities. A sharing local resource sharing method of M2M component according to an embodiment of the present invention comprises generating an replacement network service capability layer when a pre-determined component which is included in a device/gateway domain is not connected to a network domain or a pre-determined request is made; and performing communication with at least one of other components included in the device/gateway domain through the generated replacement NSCL. In exemplary embodiments of the present invention, M2M service capabilities may be replaced or changed according to system conditions.

Abstract: There is provided a system for providing information. The system includes a data classifying device configured to receive original data and classify the original data as real time data or general data; a real time data analyzing device configured to receive the real time data from the data classifying device and generate condensed information including only a part that satisfies predefined conditions among attribute information of the real time data; and a distributed parallel processing device configured to receive the general data from the data classifying device, perform a predetermined distributed parallel computation process on the general data, and generate analysis information.

Abstract: An apparatus for forecasting energy consumption includes a load data collection unit to collect low level data related to energy load data. The apparatus includes a filtering/attribute selection unit to eliminate duplicated attributes from attributes of low level data to produce an optimal attribute set. The apparatus includes a training unit produces a multi-class in which a plurality of single classes is hierarchically coupled in at least two levels and creates training data used for forecasting the energy consumption based on the produced multi-class. The apparatus includes a forecasting unit calculates the energy consumption to be forecasted on a basis of the real-time low level data, the multi-class and the training data. Therefore, it is possible to contribute to the progressive expansion and update of a cooling load forecasting system.

Abstract: A virtual sensor generation apparatus of a sensor network sets a communication connection to a sensor node at a periphery of a smart device, generates a logical sensor corresponding to a physical sensor that is connected to the sensor node, generates a virtual sensor with the logical sensor, and provides an application service to a user using the virtual sensor.