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公开(公告)号：US11604969B2
公开(公告)日：2023-03-14
申请号：US16553465
申请日：2019-08-28
Applicant: NEC Laboratories America, Inc.
Inventor： Wei Cheng , LuAn Tang , Dongjin Song , Bo Zong , Haifeng Chen , Jingchao Ni , Wenchao Yu
Abstract: Systems and methods for predicting system device failure are provided. The method includes representing device failure related data associated with the devices from a predetermined domain by temporal graphs for each of the devices. The method also includes extracting vector representations based on temporal graph features from the temporal graphs that capture both temporal and structural correlation in the device failure related data. The method further includes predicting, based on the vector representations and device failure related metrics in the predetermined domain, one or more of the devices that is expected to fail within a predetermined time.
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公开(公告)号：US11521255B2
公开(公告)日：2022-12-06
申请号：US16995052
申请日：2020-08-17
Applicant: NEC Laboratories America, Inc.
Inventor： Jingchao Ni , Haifeng Chen , Bo Zong , Xin Dong , Wei Cheng
Abstract: A method for implementing a recommendation system using an asymmetrically hierarchical network includes, for a user and an item corresponding to a user-item pair, aggregating, using asymmetrically designed sentence aggregators, respective ones of a set of item sentence embeddings and a set of user sentence embeddings to generate a set of item review embeddings based on first item attention weights and a set of user review embeddings based on first user attention weights, respectively, aggregating, using asymmetrically designed review aggregators, respective ones of the set of item review embeddings and the set of user review embeddings to generate an item embedding based on a second item attention weights and a user embedding based on second user attention weights, respectively, and predicting a rating of the user-item pair based on the item embedding and the user embedding.
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公开(公告)号：US20220237377A1
公开(公告)日：2022-07-28
申请号：US17582706
申请日：2022-01-24
Applicant: NEC Laboratories America, Inc.
Inventor： Xuchao Zhang , Bo Zong , Yanchi Liu , Haifeng Chen
IPC: G06F40/284 , G06F40/205 , G06N3/08 , G06N3/04
Abstract: Methods and systems for natural language processing include generating an encoder that includes a global part and a local part, where the global part encodes multi-hop relations between words in an input and where the local part encodes one-hop relations between words in the input. The encoder is trained to form a graph that represents tokens of an input text as nodes and that represents relations between the tokens as edges between the nodes.
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公开(公告)号：US10911488B2
公开(公告)日：2021-02-02
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: G06F11/00 , H04L29/06 , H04L12/733 , H04L12/26 , H04L12/741 , G06N20/00 , H04L12/751 , H04L12/893 , G06K9/62 , G06N3/08
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.
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公开(公告)号：US20200151563A1
公开(公告)日：2020-05-14
申请号：US16675596
申请日：2019-11-06
Applicant: NEC Laboratories America, Inc.
Inventor： Bo Zong , Jingchao Ni , Haifeng Chen , Cheng Zheng
Abstract: A method for employing a supervised graph sparsification (SGS) network to use feedback from subsequent graph learning tasks to guide graph sparsification is presented. The method includes, in a training phase, generating sparsified subgraphs by edge sampling from input training graphs following a learned distribution, feeding the sparsified subgraphs to a prediction/classification component, collecting a predication/classification error, and updating parameters of the learned distribution based on a gradient derived from the predication/classification error. The method further includes, in a testing phase, generating sparsified subgraphs by edge sampling from input testing graphs following the learned distribution, feeding the sparsified subgraphs to the prediction/classification component, and outputting prediction/classification results to a visualization device.
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Patent Agency Ranking
公开(公告)号：US20200090025A1
公开(公告)日：2020-03-19
申请号：US16553465
申请日：2019-08-28
Applicant: NEC Laboratories America, Inc.
Inventor： Wei Cheng , LuAn Tang , Dongjin Song , Bo Zong , Haifeng Chen , Jingchao Ni , Wenchao Yu
Abstract: Systems and methods for predicting system device failure are provided. The method includes representing device failure related data associated with the devices from a predetermined domain by temporal graphs for each of the devices. The method also includes extracting vector representations based on temporal graph features from the temporal graphs that capture both temporal and structural correlation in the device failure related data. The method further includes predicting, based on the vector representations and device failure related metrics in the predetermined domain, one or more of the devices that is expected to fail within a predetermined time.
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公开(公告)号：US10567409B2
公开(公告)日：2020-02-18
申请号：US15889733
申请日：2018-02-06
Applicant: NEC Laboratories America, Inc.
Abstract: A method for implementing automatic and scalable log pattern learning in security log analysis is provided. The method includes collecting security logs generated by a computer system. An incremental learning process is implemented to generate a set of log patterns from the collected security logs. The collected security logs are parsed using the set of log patterns.
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公开(公告)号：US10289841B2
公开(公告)日：2019-05-14
申请号：US15725974
申请日：2017-10-05
Applicant: NEC Laboratories America, Inc.
Inventor： LuAn Tang , Hengtong Zhang , Zhengzhang Chen , Bo Zong , Zhichun Li , Guofei Jiang , Kenji Yoshihira
Abstract: Methods and systems for detecting anomalous events include detecting anomalous events in monitored system data. An event correlation graph is generated based on the monitored system data that characterizes the tendency of processes to access system targets. Kill chains are generated that connect malicious events over a span of time from the event correlation graph that characterize events in an attack path over time by sorting events according to a maliciousness value and determining at least one sub-graph within the event correlation graph with an above-threshold maliciousness rank. A security management action is performed based on the kill chains.
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公开(公告)号：US20180365291A1
公开(公告)日：2018-12-20
申请号：US15983404
申请日：2018-05-18
Applicant: NEC Laboratories America, Inc.
Inventor： Haifeng Chen , Youfu Li , Daeki Cho , Bo Zong , Nipun Arora , Cristian Lumezanu
IPC: G06F17/30
Abstract: Systems and methods for optimizing query execution to improve query processing by a computer are provided. A query is analyzed and translated into a logical plan. A runtime query optimizer is applied to the logical plan to identify a physical plan including operators for execution. The logical plan is translated into the physical plan. Execution of the query is scheduled according to the physical plan.
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10.发明申请公开(公告)号：US20180276566A1
公开(公告)日：2018-09-27
申请号：US15874220
申请日：2018-01-18
Applicant: NEC Laboratories America, Inc.
CPC classification number: C07F1/00 , C07F1/08 , C07F3/003 , C07F3/02 , C07F3/06 , C07F5/003 , C07F7/003 , C07F7/28 , C07F9/005 , C07F11/005 , C07F13/005 , C07F15/0046 , C07F15/025 , C07F15/045 , C07F15/065 , C23C16/18 , C23C16/45553 , G05B23/0218 , G06F16/951 , G06N20/00 , H01L21/02205 , H01L21/32051
Abstract: Systems and methods for automatically generating a set of meta-parameters used to train invariant-based anomaly detectors are provided. Data is transformed into a first set of time series data and a second set of time series data. A fitness threshold search is performed on the first set of time series data to automatically generate a fitness threshold, and a time resolution search is performed on the set of second time series data to automatically generate a time resolution. A set of meta-parameters including the fitness threshold and the time resolution are sent to one or more user devices across a network to govern the training of an invariant-based anomaly detector.
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