知搜-全球专利检索

  1. Login
  2. Sign Up

Search Results

10 records (took 0.069 seconds)

    PEER RISK BENCHMARKING USING GENERATIVE ADVERSARIAL NETWORKS
    1.
    发明申请
    PEER RISK BENCHMARKING USING GENERATIVE ADVERSARIAL NETWORKS 有权

    公开(公告)号：US20220217056A1

    公开(公告)日：2022-07-07

    申请号：US17704449

    申请日：2022-03-25

    Applicant: Cisco Technology, Inc.

    Inventor： Qihong Shao ,  David John Zacks ,  Xinjun Zhang

    IPC: H04L41/14 ,  H04L41/147 ,  H04L43/06 ,  H04L41/12 ,  H04L43/045 ,  H04L41/5067 ,  H04L43/0817 ,  H04L43/55

    Abstract: A method, computer system, and computer program product are provided for peer risk benchmarking. Customer data for a first network is obtained, wherein the customer data comprises a role of one or more network devices in the first network and a plurality of risk reports corresponding to the one or more network devices, and wherein each risk report is associated with a particular dimension of a plurality of dimensions of risk for the one or more network devices. A network profile image is generated by processing the plurality of risk reports. A generative adversarial network generates a synthetic network profile image from the network profile image, wherein the synthetic network profile image does not include the customer data. A second network is evaluated using the synthetic network profile image to identify differences between the first network and the second network.

    PEER RISK BENCHMARKING USING GENERATIVE ADVERSARIAL NETWORKS
    4.
    发明申请
    PEER RISK BENCHMARKING USING GENERATIVE ADVERSARIAL NETWORKS 有权

    公开(公告)号：US20230118857A1

    公开(公告)日：2023-04-20

    申请号：US18067068

    申请日：2022-12-16

    Applicant: Cisco Technology, Inc.

    Inventor： Qihong Shao ,  David John Zacks ,  Xinjun Zhang

    IPC: H04L41/14 ,  H04L41/12 ,  H04L41/147 ,  H04L41/5067 ,  H04L43/045 ,  H04L43/06 ,  H04L43/0817 ,  H04L43/55

    Abstract: A method, computer system, and computer program product are provided for peer risk benchmarking. Customer data for a first network is obtained, wherein the customer data comprises a role of one or more network devices in the first network and a plurality of risk reports corresponding to the one or more network devices, and wherein each risk report is associated with a particular dimension of a plurality of dimensions of risk for the one or more network devices. A network profile image is generated by processing the plurality of risk reports. A generative adversarial network generates a synthetic network profile image from the network profile image, wherein the synthetic network profile image does not include the customer data. A second network is evaluated using the synthetic network profile image to identify differences between the first network and the second network.

    Peer risk benchmarking using generative adversarial networks
    5.
    发明授权
    Peer risk benchmarking using generative adversarial networks 有权

    公开(公告)号：US11533241B2

    公开(公告)日：2022-12-20

    申请号：US17704449

    申请日：2022-03-25

    Applicant: Cisco Technology, Inc.

    Inventor： Qihong Shao ,  David John Zacks ,  Xinjun Zhang

    IPC: G06F15/173 ,  H04L41/14 ,  H04L41/12 ,  H04L41/147 ,  H04L41/5067 ,  H04L43/045 ,  H04L43/06 ,  H04L43/0817 ,  H04L43/55

    Abstract: A method, computer system, and computer program product are provided for peer risk benchmarking. Customer data for a first network is obtained, wherein the customer data comprises a role of one or more network devices in the first network and a plurality of risk reports corresponding to the one or more network devices, and wherein each risk report is associated with a particular dimension of a plurality of dimensions of risk for the one or more network devices. A network profile image is generated by processing the plurality of risk reports. A generative adversarial network generates a synthetic network profile image from the network profile image, wherein the synthetic network profile image does not include the customer data. A second network is evaluated using the synthetic network profile image to identify differences between the first network and the second network.

    PEER RISK BENCHMARKING USING GENERATIVE ADVERSARIAL NETWORKS
    7.
    发明申请
    PEER RISK BENCHMARKING USING GENERATIVE ADVERSARIAL NETWORKS 有权

    公开(公告)号：US20220131761A1

    公开(公告)日：2022-04-28

    申请号：US17077073

    申请日：2020-10-22

    Applicant: Cisco Technology, Inc.

    Inventor： Qihong Shao ,  David John Zacks ,  Xinjun Zhang

    IPC: H04L12/24 ,  H04L12/26

    Abstract: A method, computer system, and computer program product are provided for peer risk benchmarking. Customer data for a first network is obtained, wherein the customer data comprises a role of one or more network devices in the first network and a plurality of risk reports corresponding to the one or more network devices, and wherein each risk report is associated with a particular dimension of a plurality of dimensions of risk for the one or more network devices. A network profile image is generated by processing the plurality of risk reports. A generative adversarial network generates a synthetic network profile image from the network profile image, wherein the synthetic network profile image does not include the customer data. A second network is evaluated using the synthetic network profile image to identify differences between the first network and the second network.

    Peer risk benchmarking using generative adversarial networks
    8.
    发明授权
    Peer risk benchmarking using generative adversarial networks 有权

    公开(公告)号：US11316750B1

    公开(公告)日：2022-04-26

    申请号：US17077073

    申请日：2020-10-22

    Applicant: Cisco Technology, Inc.

    Inventor： Qihong Shao ,  David John Zacks ,  Xinjun Zhang

    IPC: G06F15/173 ,  H04L41/14 ,  H04L41/12 ,  H04L41/147 ,  H04L43/0817 ,  H04L41/5067 ,  H04L43/045 ,  H04L43/06 ,  H04L43/55

    Abstract: A method, computer system, and computer program product are provided for peer risk benchmarking. Customer data for a first network is obtained, wherein the customer data comprises a role of one or more network devices in the first network and a plurality of risk reports corresponding to the one or more network devices, and wherein each risk report is associated with a particular dimension of a plurality of dimensions of risk for the one or more network devices. A network profile image is generated by processing the plurality of risk reports. A generative adversarial network generates a synthetic network profile image from the network profile image, wherein the synthetic network profile image does not include the customer data. A second network is evaluated using the synthetic network profile image to identify differences between the first network and the second network.

    TAILORED NETWORK RISK ANALYSIS USING DEEP LEARNING MODELING
    10.
    发明申请
    TAILORED NETWORK RISK ANALYSIS USING DEEP LEARNING MODELING 有权

    公开(公告)号：US20220103586A1

    公开(公告)日：2022-03-31

    申请号：US17034241

    申请日：2020-09-28

    Applicant: Cisco Technology, Inc.

    Inventor： Qihong Shao ,  David John Zacks ,  Yue Liu ,  Xinjun Zhang

    IPC: H04L29/06 ,  H04L12/26 ,  G06N3/02 ,  G06F40/30 ,  G06K9/62

    Abstract: A method, computer system, and computer program product are provided for network risk analysis. A plurality of risk reports relating to a network device in a network are obtained, wherein each risk report is associated with a particular dimension of a plurality of dimensions of risk for the network device in the network. A count of the plurality of risk reports is determined for each dimension of the plurality of dimensions of risk. A regression model is applied to determine a risk value for the network device in the network based on the count of the plurality of risk reports for each dimension and based a role of the network device in the network.

Patent Agency Ranking