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    Density estimation network for unsupervised anomaly detection
    1.
    发明授权
    Density estimation network for unsupervised anomaly detection 有权

    公开(公告)号：US10999247B2

    公开(公告)日：2021-05-04

    申请号：US16169012

    申请日：2018-10-24

    Applicant: NEC Laboratories America, Inc.

    Inventor： Bo Zong ,  Daeki Cho ,  Cristian Lumezanu ,  Haifeng Chen ,  Qi Song

    IPC: H04L29/06 ,  G06N3/08 ,  G06N3/04

    Abstract: Systems and methods for preventing cyberattacks using a Density Estimation Network (DEN) for unsupervised anomaly detection, including constructing the DEN using acquired network traffic data by performing end-to-end training. The training includes generating low-dimensional vector representations of the network traffic data by performing dimensionality reduction of the network traffic data, predicting mixture membership distribution parameters for each of the low-dimensional representations by performing density estimation using a Gaussian Mixture Model (GMM) framework, and formulating an objective function to estimate an energy and determine a density level of the low-dimensional representations for anomaly detection, with an anomaly being identified when the energy exceeds a pre-defined threshold. Cyberattacks are prevented by blocking transmission of network flows with identified anomalies by directly filtering out the flows using a network traffic monitor.

    NEURAL NETWORK BASED SPOOFING DETECTION
    2.
    发明申请
    NEURAL NETWORK BASED SPOOFING DETECTION 审中-公开

    公开(公告)号：US20190098048A1

    公开(公告)日：2019-03-28

    申请号：US16101794

    申请日：2018-08-13

    Applicant: NEC Laboratories America, Inc.

    Inventor： Cristian Lumezanu ,  Nipun Arora ,  Haifeng Chen ,  Bo Zong ,  Daeki Cho ,  Mingda Li

    IPC: H04L29/06 ,  H04L12/733 ,  H04L12/741 ,  H04L12/26 ,  G06N3/08 ,  G06K9/62

    Abstract: Methods and systems for mitigating a spoofing-based attack include calculating a travel distance between a source Internet Protocol (IP) address and a target IP address from a received packet based on time-to-live information from the received packet. An expected travel distance between the source IP address and the target IP address is estimated based on a sparse set of known source/target distances. It is determined that the received packet has a spoofed source IP address based on a comparison between the calculated travel distance and the expected travel distance. A security action is performed responsive to the determination that the received packet has a spoofed source IP address.

    Network gateway spoofing detection and mitigation
    3.
    发明授权
    Network gateway spoofing detection and mitigation 有权

    公开(公告)号：US10999323B2

    公开(公告)日：2021-05-04

    申请号：US16101834

    申请日：2018-08-13

    Applicant: NEC Laboratories America, Inc.

    Inventor： Cristian Lumezanu ,  Nipun Arora ,  Haifeng Chen ,  Bo Zong ,  Daeki Cho ,  Mingda Li

    IPC: G06F21/00 ,  H04L29/06 ,  H04L12/733 ,  H04L12/26 ,  H04L12/741 ,  G06N20/00 ,  H04L12/751 ,  H04L12/893 ,  G06K9/62 ,  G06N3/08

    Abstract: Endpoint security systems and methods include a distance estimation module configured to calculate a travel distance between a source Internet Protocol (IP) address and an IP address for a target network endpoint system from a received packet received by a network gateway system based on time-to-live (TTL) information from the received packet. A machine learning model is configured to estimate an expected travel distance between the source IP address and the target network endpoint system IP address based on a sparse set of known source/target distances. A spoof detection module is configured to determine that the received packet has a spoofed source IP address based on a comparison between the calculated travel distance and the expected travel distance. A security module is configured to perform a security action at the network gateway system responsive to the determination that the received packet has a spoofed source IP address.

    Network endpoint spoofing detection and mitigation
    7.
    发明授权
    Network endpoint spoofing detection and mitigation 有权

    公开(公告)号：US10887344B2

    公开(公告)日：2021-01-05

    申请号：US16101815

    申请日：2018-08-13

    Applicant: NEC Laboratories America, Inc.

    Inventor： Cristian Lumezanu ,  Nipun Arora ,  Haifeng Chen ,  Bo Zong ,  Daeki Cho ,  Mingda Li

    IPC: H04L29/00 ,  H04L29/06 ,  H04L12/733 ,  H04L12/26 ,  H04L12/741 ,  G06N20/00 ,  H04L12/751 ,  H04L12/893 ,  G06K9/62 ,  G06N3/08

    Abstract: Endpoint security systems and methods include a distance estimation module configured to calculate a travel distance between a source Internet Protocol (IP) address and an IP address for a target network endpoint system from a received packet received by the target network endpoint system based on time-to-live (TTL) information from the received packet. A machine learning model is configured to estimate an expected travel distance between the source IP address and the target network endpoint system IP address based on a sparse set of known source/target distances. A spoof detection module is configured to determine that the received packet has a spoofed source IP address based on a comparison between the calculated travel distance and the expected travel distance. A security module is configured to perform a security action at the target network endpoint system responsive to the determination that the received packet has a spoofed source IP address.

    NETWORK GATEWAY SPOOFING DETECTION AND MITIGATION
    8.
    发明申请
    NETWORK GATEWAY SPOOFING DETECTION AND MITIGATION 审中-公开

    公开(公告)号：US20190098050A1

    公开(公告)日：2019-03-28

    申请号：US16101834

    申请日：2018-08-13

    Applicant: NEC Laboratories America, Inc.

    Inventor： Cristian Lumezanu ,  Nipun Arora ,  Haifeng Chen ,  Bo Zong ,  Daeki Cho ,  Mingda Li

    IPC: H04L29/06 ,  H04L12/733 ,  H04L12/741 ,  H04L12/26 ,  G06F15/18

    Abstract: Endpoint security systems and methods include a distance estimation module configured to calculate a travel distance between a source Internet Protocol (IP) address and an IP address for a target network endpoint system from a received packet received by a network gateway system based on time-to-live (TTL) information from the received packet. A machine learning model is configured to estimate an expected travel distance between the source IP address and the target network endpoint system IP address based on a sparse set of known source/target distances. A spoof detection module is configured to determine that the received packet has a spoofed source IP address based on a comparison between the calculated travel distance and the expected travel distance. A security module is configured to perform a security action at the network gateway system responsive to the determination that the received packet has a spoofed source IP address.

    DENSITY ESTIMATION NETWORK FOR UNSUPERVISED ANOMALY DETECTION
    9.
    发明申请
    DENSITY ESTIMATION NETWORK FOR UNSUPERVISED ANOMALY DETECTION 审中-公开

    公开(公告)号：US20190124045A1

    公开(公告)日：2019-04-25

    申请号：US16169012

    申请日：2018-10-24

    Applicant: NEC Laboratories America, Inc.

    Inventor： Bo Zong ,  Daeki Cho ,  Cristian Lumezanu ,  Haifeng Chen ,  Qi Song

    IPC: H04L29/06 ,  G06N3/08 ,  G06N3/04

    Abstract: Systems and methods for preventing cyberattacks using a Density Estimation Network (DEN) for unsupervised anomaly detection, including constructing the DEN using acquired network traffic data by performing end-to-end training. The training includes generating low-dimensional vector representations of the network traffic data by performing dimensionality reduction of the network traffic data, predicting mixture membership distribution parameters for each of the low-dimensional representations by performing density estimation using a Gaussian Mixture Model (GMM) framework, and formulating an objective function to estimate an energy and determine a density level of the low-dimensional representations for anomaly detection, with an anomaly being identified when the energy exceeds a pre-defined threshold. Cyberattacks are prevented by blocking transmission of network flows with identified anomalies by directly filtering out the flows using a network traffic monitor.

    NETWORK ENDPOINT SPOOFING DETECTION AND MITIGATION
    10.
    发明申请
    NETWORK ENDPOINT SPOOFING DETECTION AND MITIGATION 审中-公开

    公开(公告)号：US20190098049A1

    公开(公告)日：2019-03-28

    申请号：US16101815

    申请日：2018-08-13

    Applicant: NEC Laboratories America, Inc.

    Inventor： Cristian Lumezanu ,  Nipun Arora ,  Haifeng Chen ,  Bo Zong ,  Daeki Cho ,  Mingda Li

    IPC: H04L29/06 ,  H04L12/733 ,  H04L12/751 ,  H04L12/893

    Abstract: Endpoint security systems and methods include a distance estimation module configured to calculate a travel distance between a source Internet Protocol (IP) address and an IP address for a target network endpoint system from a received packet received by the target network endpoint system based on time-to-live (TTL) information from the received packet. A machine learning model is configured to estimate an expected travel distance between the source IP address and the target network endpoint system IP address based on a sparse set of known source/target distances. A spoof detection module is configured to determine that the received packet has a spoofed source IP address based on a comparison between the calculated travel distance and the expected travel distance. A security module is configured to perform a security action at the target network endpoint system responsive to the determination that the received packet has a spoofed source IP address.

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