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    APPARATUS AND METHOD FOR DETECTING TRAFFIC FLOODING ATTACK AND CONDUCTING IN-DEPTH ANALYSIS USING DATA MINING
    1.
    发明申请
    APPARATUS AND METHOD FOR DETECTING TRAFFIC FLOODING ATTACK AND CONDUCTING IN-DEPTH ANALYSIS USING DATA MINING 有权
    用于检测交通流量攻击和使用数据挖掘进行深入分析的装置和方法

    公开(公告)号：US20130291108A1

    公开(公告)日：2013-10-31

    申请号：US13869151

    申请日：2013-04-24

    Applicant: Electronics and Telecommunications Research Institute

    Inventor： Jae Hak YU ,  Byung Bog LEE ,  Hyo Chan BANG

    IPC: G06F21/55

    CPC classification number: G06F21/55 ,  H04L63/1408 ,  H04L63/1458

    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 translation: 提供了一种用于检测流量泛滥攻击的装置和方法，并且使用可以快速检测分布式拒绝服务（DDoS）攻击的数据挖掘进行深入分析，例如，流量洪泛攻击，其更加不同于和 拒绝服务（DoS）攻击，执行攻击类型分类，并对攻击进行语义分析。 该装置和方法可以通过快速检测流量泛滥攻击，对攻击类型进行分类，并且基于数据挖掘的预测和分析方案进行语义分析，来支持系统操作并提供更稳定的服务。

    METHOD AND SYSTEM FOR ANALYZING DATA
    3.
    发明申请
    METHOD AND SYSTEM FOR ANALYZING DATA 审中-公开

    公开(公告)号：US20170330086A1

    公开(公告)日：2017-11-16

    申请号：US15592342

    申请日：2017-05-11

    Applicant: ELECTRONICS AND TELECOMMUNICATIONS RESEARCH INSTITUTE

    Inventor： Yoon Mee DOH ,  Jae Hak YU ,  Kye Seon LEE

    IPC: G06N5/02

    CPC classification number: G06N5/022

    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.

    APPARATUS AND METHOD FOR FORECASTING ENERGY CONSUMPTION
    4.
    发明申请
    APPARATUS AND METHOD FOR FORECASTING ENERGY CONSUMPTION 审中-公开
    用于预测能源消耗的装置和方法

    公开(公告)号：US20140095415A1

    公开(公告)日：2014-04-03

    申请号：US13916309

    申请日：2013-06-12

    Applicant: Electronics and Telecommunications Research Institute

    Inventor： Jae Hak YU ,  Byung Bog LEE ,  Yoon Sik YOO ,  Hyochan BANG

    IPC: G06N99/00

    CPC classification number: G06N20/00

    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 translation: 用于预测能量消耗的装置包括负载数据收集单元，用于收集与能量负荷数据相关的低电平数据。 该装置包括滤波/属性选择单元，以从低级数据的属性中消除重复的属性以产生最佳属性集。 所述装置包括训练单元，其产生多级，其中多个单个类别在至少两个级别中被分层耦合，并且创建用于基于所产生的多类预测能量消耗的训练数据。 该装置包括预测单元，基于实时低电平数据，多级和训练数据来计算要预测的能量消耗。 因此，可以有助于冷却负荷预测系统的逐渐扩展和更新。

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