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    CONTENT CACHING OPTIMIZATION SYSTEM AND METHOD
    71.
    发明公开
    CONTENT CACHING OPTIMIZATION SYSTEM AND METHOD 审中-公开

    公开(公告)号：US20240137424A1

    公开(公告)日：2024-04-25

    申请号：US18086493

    申请日：2022-12-21

    Applicant: Foundation of Soongsil University-Industry Cooperation

    Inventor： Yun Won CHUNG ,  Min Wook KANG

    IPC: H04L67/568 ,  H04L41/122 ,  H04L67/63

    CPC classification number: H04L67/568 ,  H04L41/122 ,  H04L67/63

    Abstract: Provided are a content caching optimization system and method. The content caching optimization system in which content priority in an information-centric networking (ICN) environment is taken into consideration includes one or more producer terminals configured to generate and provide content, one or more user terminals configured to transmit content requests according to users and receive content according to the content requests, one or more mobilelmultiple access edge cotnputings (MECs) configured to predict the number of requests for each piece of content to be requested later on the basis of the content requests received from the user terminals, and a software-defined network (SDN) controller configured to calculate a content popularity using the number of requests for each piece of content predicted by the MECs and perform content caching optimization on the basis of the calculated content popularity and a preset content priority.

    APPARATUS AND METHOD FOR INFERRING DRIVING CHARACTERISTICS OF A VEHICLE
    74.
    发明公开
    APPARATUS AND METHOD FOR INFERRING DRIVING CHARACTERISTICS OF A VEHICLE 审中-公开

    公开(公告)号：US20230406327A1

    公开(公告)日：2023-12-21

    申请号：US17959515

    申请日：2022-10-04

    Applicant: FOUNDATION OF SOONGSIL UNIVERSITY-INDUSTRY COOPERATION

    Inventor： Minhae KWON ,  Dongsu LEE

    IPC: B60W50/00 ,  G08G1/01 ,  G08G1/052 ,  G05B13/02

    CPC classification number: B60W50/00 ,  G08G1/0116 ,  G08G1/0133 ,  G08G1/052 ,  G05B13/0265 ,  B60W60/001

    Abstract: The present disclosure relates to a driving characteristic inference apparatus and method of a vehicle. According to an exemplary embodiment of the present disclosure, a driving characteristic inference method includes observing a target driving vehicle which is an observation target to generate driving data including behavior information of the target driving vehicle, by an observation module; performing reinforcement learning on an artificial intelligence model using learning data including a first driving characteristic coefficient, by a learning module; generating sampled inference behavior data with the driving data and the first driving character coefficient as an input of the artificial intelligence model, by a model utilization module; and comparing the generated inference behavior data with measured actual behavior data to determine the second driving characteristic coefficient, by an inference module.

    Mobile malicious code classification method based on feature selection and recording medium and device for performing the same
    75.
    发明授权
    Mobile malicious code classification method based on feature selection and recording medium and device for performing the same 有权

    公开(公告)号：US11809557B2

    公开(公告)日：2023-11-07

    申请号：US17296892

    申请日：2021-01-29

    Applicant: Foundation of Soongsil University-Industry Cooperation

    Inventor： Jeong Hyun Yi ,  Eun Byeol Ko

    IPC: G06F21/56 ,  G06N3/08

    CPC classification number: G06F21/562 ,  G06N3/08 ,  G06F2221/033

    Abstract: A mobile malicious code classification method based on feature selection includes extracting Application Programming Interface (API) feature information including a package name, a class name, a method name and a description from a malicious application of a predefined category, vectorizing a training dataset generated using the package name, the class name and the method name in the API feature information for deep learning, learning the vectorized training dataset to generate a classifier, probabilistically classifying to fit a target malicious application into a category, and defining the category of the target malicious application using a result of the classification and outputting a classification important API. Accordingly, it is possible to deal with malicious behaviors of malicious applications quickly and prevent damage caused by the malicious behaviors.

    ON-DEVICE ANDROID MALWARE DETECTION METHOD BASED ON ADAPTIVE MODEL THROUGH TRANSFER LEARNING, AND RECORDING MEDIUM AND APPARATUS FOR PERFORMING THE SAME
    76.
    发明公开
    ON-DEVICE ANDROID MALWARE DETECTION METHOD BASED ON ADAPTIVE MODEL THROUGH TRANSFER LEARNING, AND RECORDING MEDIUM AND APPARATUS FOR PERFORMING THE SAME 审中-公开

    公开(公告)号：US20230177156A1

    公开(公告)日：2023-06-08

    申请号：US17888983

    申请日：2022-08-16

    Applicant: Foundation of Soongsil University-Industry Cooperation

    Inventor： Soohwan JUNG ,  Hyunseok SHIM ,  Songi GWAK

    IPC: G06F21/56

    CPC classification number: G06F21/563 ,  G06F2221/033

    Abstract: Provided is an on-device Android malware detection method based on an adaptive model through transfer learning, including: determining whether an application is malicious or unfavorable from a list of applications installed on a device; decompiling, in the device, an Android package (APK) of the application installed on the device; transmitting the determined list and the decompiled APK file to a server in order to generate a head model in the server and use the generated head model for the transfer learning with a base model; performing malware analysis in the device using a transfer learning model received from the server for an application newly installed on the device; and providing a malware analysis result to a user through the device as a result, and since the malware analysis is performed on the device, it is possible to ensure the availability and real-time performance of enabling analysis outside of a network range.

    METHOD AND APPARATUS FOR MANAGING A YAML FILE FOR KUBERNETES
    77.
    发明申请
    METHOD AND APPARATUS FOR MANAGING A YAML FILE FOR KUBERNETES 有权

    公开(公告)号：US20230117114A1

    公开(公告)日：2023-04-20

    申请号：US17867465

    申请日：2022-07-18

    Applicant: FOUNDATION OF SOONGSIL UNIVERSITY INDUSTRY COOPERATION

    Inventor： Myung Sik YOO ,  Le Van CUONG

    IPC: G06F40/143 ,  G06F9/451 ,  G06F9/50

    Abstract: The present subject matter relates to a method and apparatus for managing a YAML file for Kubernetis. According to the present subject matter, the apparatus comprises a front-end component for providing a visual interface to a client, creating a YAML file in accordance with user input through the visual interface, and transforming the generated YAML file into a JavaScript Object Notation (JSON) form; and a back-end component for storing the YAML file transformed into the JSON form in a database, checking, applying and removing the YAML file, and applying the YAML file to a plurality of Kubernetes clusters such that the YAML file is executed.

    Triple verification device and triple verification method
    78.
    发明授权
    Triple verification device and triple verification method 有权

    公开(公告)号：US11562177B2

    公开(公告)日：2023-01-24

    申请号：US16697238

    申请日：2019-11-27

    Applicant: Foundation of Soongsil University-Industry Cooperation

    Inventor： Young Tack Park ,  Jagvaral Batselem ,  Wan Gon Lee

    IPC: G06K9/00 ,  G06K9/62 ,  G06N3/08 ,  G06N3/04 ,  G06F17/16 ,  G06N20/20 ,  G06N20/10 ,  G06N5/04

    Abstract: A triple verification method is provided. The triple verification method includes setting a triple having a source entity, a target entity, and a relation value between the source entity and the target entity by a setting unit, extracting a plurality of intermediate entities associated with the source entity and the target entity by the setting unit, defining a connection relation between the intermediate entity, the source entity, and the target entity and generating a plurality of connection paths connecting the source entity, the intermediate entity, and the target entity by a path generation unit, generating a matrix by embedding the plurality of connection paths into vector values by a first processing unit, calculating a feature map by performing a convolution operation on the matrix by a second processing unit, generating an encoding vector for each connection path by encoding the feature map by applying a bidirectional long short-term memory neural network (BiLSTM) technique by a third processing unit, and generating a state vector by summing the encoding vectors for each connection path by applying an attention mechanism and verifying the triple based on a similarity value between the relation value of the triple and the state vector by a determination unit.

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