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    Provenance-based threat detection tools and stealthy malware detection
    112.
    发明授权
    Provenance-based threat detection tools and stealthy malware detection 有权

    公开(公告)号：US11423146B2

    公开(公告)日：2022-08-23

    申请号：US16991288

    申请日：2020-08-12

    Applicant: NEC Laboratories America, Inc.

    Inventor： Ding Li ,  Xiao Yu ,  Junghwan Rhee ,  Haifeng Chen ,  Qi Wang

    IPC: G06F21/56 ,  G06F21/55 ,  G06K9/62 ,  G06F21/54

    Abstract: Systems and methods for a provenance based threat detection tool that builds a provenance graph including a plurality of paths using a processor device from provenance data obtained from one or more computer systems and/or networks; samples the provenance graph to form a plurality of linear sample paths, and calculates a regularity score for each of the plurality of linear sample paths using a processor device; selects a subset of linear sample paths from the plurality of linear sample paths based on the regularity score, and embeds each of the subset of linear sample paths by converting each of the subset of linear sample paths into a numerical vector using a processor device; detects anomalies in the embedded paths to identify malicious process activities, and terminates a process related to the embedded path having the identified malicious process activities.

    PHYSIMETRIC-BASED DATA SECURITY FOR CODED DISTRIBUTED TEMPERATURE SENSING
    113.
    发明申请
    PHYSIMETRIC-BASED DATA SECURITY FOR CODED DISTRIBUTED TEMPERATURE SENSING 有权

    公开(公告)号：US20220247562A1

    公开(公告)日：2022-08-04

    申请号：US17589863

    申请日：2022-01-31

    Applicant: NEC Laboratories America, Inc.

    Inventor： Qiang WANG ,  Junqiang HU ,  Jian FANG ,  Yaowen LI ,  Ting WANG

    IPC: H04L9/32 ,  G01K11/32

    Abstract: Physimetric-based data security for coded distributed temperature sensing (DTS) in which physimetric information is extracted from a coded-DTS interrogator which is unique for each interrogator at each operating run time—and used to reconstruct a final temperature determination from DTS data. The physimetric information includes coded-DTS pulse code and coded-DTS pulse profile information as a key to permit secure sharing with authorized users. The pulse code and pulse profile information are encrypted and made available to an authorized user. The authorized user can then decrypt the pulse code and pulse profile information and subsequently use this key information (pulse profile and pulse code files) to retrieve temperature information from for example, a remote computer providing a continuous raw data feed—without being susceptible to eavesdropping. The pulse profile and pulse code files permit reconstruction of temperature from DTS continuous raw data feed which have no meaningful informational value to an eavesdropper who has no access to the unencrypted pulse profile and pulse code information.

    INTERPRETING CROSS-LINGUAL MODELS FOR NATURAL LANGUAGE INFERENCE
    114.
    发明申请
    INTERPRETING CROSS-LINGUAL MODELS FOR NATURAL LANGUAGE INFERENCE 有权

    公开(公告)号：US20220237391A1

    公开(公告)日：2022-07-28

    申请号：US17582464

    申请日：2022-01-24

    Applicant: NEC Laboratories America, Inc.

    Inventor： Xuchao Zhang ,  Bo Zong ,  Haifeng Chen ,  Yanchi Liu

    IPC: G06F40/58 ,  G06F40/30 ,  G06F40/284

    Abstract: Systems and methods are provided for Cross-lingual Transfer Interpretation (CTI). The method includes receiving text corpus data including premise-hypothesis pairs with a relationship label in a source language, and conducting a source to target language translation. The method further includes performing a feature importance extraction, where an integrated gradient is applied to assign an importance score to each input feature, and performing a cross-lingual feature alignment, where tokens in the source language are aligned with tokens in the target language for both the premise and the hypothesis based on semantic similarity. The method further includes performing a qualitative analysis, where the importance score of each token can be compared between the source language and the target language according to a feature alignment result.

    VIBRATION DETECTION USING PHASE RECOVERED FROM AN OPTICAL TRANSPONDER WITH COHERENT DETECTION
    115.
    发明申请
    VIBRATION DETECTION USING PHASE RECOVERED FROM AN OPTICAL TRANSPONDER WITH COHERENT DETECTION 有权

    公开(公告)号：US20220236083A1

    公开(公告)日：2022-07-28

    申请号：US17544806

    申请日：2021-12-07

    Applicant: NEC Laboratories America, Inc.

    Inventor： Ezra IP ,  Yue-Kai HUANG

    IPC: G01D5/353 ,  H04B10/61 ,  G01H9/00

    Abstract: Aspects of the present disclosure describe systems, methods. and structures for vibration detection using phase recovered from an optical transponder with coherent detection. Advantageously, our systems, methods, and structures leverage contemporary digital coherent receiver architecture in which various adaptive DSP operations performed to recover transmitted data track optical phase. The phase is extracted at low overhead cost, allowing a digital coherent transponder to perform vibration detection/monitoring as an auxiliary function to data transmission. Demonstration of vibration detection and localization based on the extraction of optical phase from payload-carrying telecommunications signal using a coherent receiver in a bidirectional WDM transmission system is shown and described.

    Topology-inspired neural network autoencoding for electronic system fault detection
    119.
    发明授权
    Topology-inspired neural network autoencoding for electronic system fault detection 有权

    公开(公告)号：US11379284B2

    公开(公告)日：2022-07-05

    申请号：US16245734

    申请日：2019-01-11

    Applicant: NEC Laboratories America, Inc.

    Inventor： Wei Cheng ,  Haifeng Chen ,  Masanao Natsumeda

    IPC: G06F11/07 ,  H04L67/12 ,  G06K9/62 ,  G06N3/08

    Abstract: Systems and methods for fault detection in a sensor network include receiving sensor data from sensors in the sensor network with a communication device. The sensor data is analyze to determine if the sensor data is indicative of a fault with a fault detection model, the fault detection model including; predicting the sensor data with an autoencoder by encoding the sensor data and decoding encoded the sensor data, autoregressively model the sensor data with an autoregressor, combining the modeled sensor data and the predicted sensor data with a combiner to produce reconstructed sensor data, and comparing the reconstructed sensor data to the sensor data with an anomaly evaluator to determine anomalies. An anomaly classification is produced by comparing the anomalies to historical anomalies with an anomaly classifier. Faults in the sensor network are automatically mitigated with a processing device based on the anomaly classification.

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