Method for processing data by edge node in network including plurality of terminals and edge node

    公开(公告)号:US11470177B2

    公开(公告)日:2022-10-11

    申请号:US16798972

    申请日:2020-02-24

    Abstract: The present disclosure provides a method for processing data by an edge node including: receiving a data request from an application; confirming whether first data corresponding to the data request is included in a content storage of the edge node; confirming whether there is second data having a correlation with the first data which is equal to or higher than a predetermined threshold value based on a previously stored mapping table when the first data is not included in the content storage of the edge node; and transmitting the second data to the application when there is the second data having the correlation with the first data which is equal to or higher than the threshold value.

    DEVICE FOR AUTOMATICALLY IDENTIFYING ANTI-ANALYSIS TECHNIQUES BY USING SIGNATURE EXTRACTION AND METHOD THEREFOR

    公开(公告)号:US20210141875A1

    公开(公告)日:2021-05-13

    申请号:US17262745

    申请日:2018-11-26

    Abstract: A device for automatically identifying anti-analysis techniques by using the signature extraction, includes an extraction unit which extracts a DEX file and an ELF file from an application file after unpacking the application file, which is in an APK format and includes compressed execution code to be executed on Android, a detection unit which receives the acquired signature classified according to types of the signature, analytically compares the input signature with the signature stored in a database, and detects the signature used in anti-analysis techniques, and a determination unit which determines according to the detected signature what anti-analysis technique is applied to the application. According to the present invention, it is possible to enable an appropriate and quick response to damages due to malicious applications by shortening the time required for analysis and automatically recognizing the application to which the anti-analysis technique is applied.

    METHOD FOR PROCESSING DATA BY EDGE NODE IN NETWORK INCLUDING PLURALITY OF TERMINALS AND EDGE NODE

    公开(公告)号:US20210120095A1

    公开(公告)日:2021-04-22

    申请号:US16798972

    申请日:2020-02-24

    Abstract: The present disclosure provides a method for processing data by an edge node including: receiving a data request from an application; confirming whether first data corresponding to the data request is included in a content storage of the edge node;
    confirming whether there is second data having a correlation with the first data which is equal to or higher than a predetermined threshold value based on a previously stored mapping table when the first data is not included in the content storage of the edge node; and transmitting the second data to the application when there is the second data having the correlation with the first data which is equal to or higher than the threshold value.

    TRIPLE VERIFICATION DEVICE AND TRIPLE VERIFICATION METHOD

    公开(公告)号:US20210064935A1

    公开(公告)日:2021-03-04

    申请号:US16697238

    申请日:2019-11-27

    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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