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公开(公告)号：US20220019892A1
公开(公告)日：2022-01-20
申请号：US17379078
申请日：2021-07-19
Applicant: NEC Laboratories America, Inc.
Inventor： Jingchao Ni , Wei Cheng , Haifeng Chen , Bo Zong
Abstract: A method for training a predictive model includes training a dual-channel neural network model, which includes a static channel to process static information and a dynamic channel to process temporal information, to generate a probability score that characterizes a likelihood of a health event occurring during a dialysis procedure, based on static profile information and temporal measurement information. An augmented model is trained to generate an importance score associated with the probability score, based on the static profile information and the temporal measurement information.
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公开(公告)号：US11221617B2
公开(公告)日：2022-01-11
申请号：US16653033
申请日：2019-10-15
Applicant: NEC Laboratories America, Inc.
Inventor： Wenchao Yu , Jingchao Ni , Bo Zong , Wei Cheng , Haifeng Chen , LuAn Tang
IPC: G05B23/02 , G06N20/10 , G06F16/901 , G06K9/62 , G06F17/18
Abstract: Systems and methods for predicting system device failure are provided. The method includes performing graph-based predictive maintenance (GBPM) to determine a trained ensemble classification model for detecting maintenance ready components that includes extracted node features and graph features. The method includes constructing, based on testing data and the trained ensemble classification model, an attributed temporal graph and the extracted node features and graph features. The method further includes concatenating the extracted node features and graph features. The method also includes determining, based on the trained ensemble classification model, a list of prediction results of components that are to be scheduled for component maintenance.
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公开(公告)号：US11171977B2
公开(公告)日：2021-11-09
申请号：US16246774
申请日：2019-01-14
Applicant: NEC Laboratories America, Inc.
Inventor： Haifeng Chen , Bo Zong , Christian Lumezanu
IPC: H04L29/06 , G06N20/00 , H04W12/122
Abstract: A method for detecting spoofing attacks from network traffic log data is presented. The method includes training a spoofing attack detector with the network traffic log data received from one or more mobile networks by extracting features that are relevant to spoofing attacks for training data, building a first set of vector representations for the network traffic log data, training an anomaly detection model by employing DAGMM, and obtaining learned parameters of DAGMM. The method includes testing the spoofing attack detector with the network traffic log data received from the one or more mobile networks by extracting features that are relevant to spoofing attacks for testing data, building a second set of vector representations for the network traffic log data, obtaining latent representations of the testing data, computing a z-score of the testing data, and creating a spoofing attack alert report listing traffic logs generating z-scores exceeding a predetermined threshold.
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公开(公告)号：US20210255363A1
公开(公告)日：2021-08-19
申请号：US17165515
申请日：2021-02-02
Applicant: NEC Laboratories America, Inc.
Inventor： Yanchi Liu , Jingchao Ni , Bo Zong , Haifeng Chen , Zhengzhang Chen , Wei Cheng , Denghui Zhang
Abstract: A method for employing a unified semi-supervised deep learning (DL) framework for turbulence forecasting is presented. The method includes extracting historical and forecasted weather features of a spatial region, calculating turbulence indexes to fill feature cubes, each feature cube representing a grid-based 3D region, and building an encoder-decoder framework based on convolutional long short-term memory (ConvLSTM) to model spatio-temporal correlations or patterns causing turbulence. The method further includes employing a dual label guessing component to dynamically integrate complementary signals from a turbulence forecasting network and a turbulence detection network to generate pseudo-labels, reweighing the generated pseudo-labels by a heuristic label quality detector based on KL-Divergence, applying a hybrid loss function to predict turbulence conditions, and generating a turbulence dataset including the predicted turbulence conditions.
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公开(公告)号：US20210065278A1
公开(公告)日：2021-03-04
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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Patent Agency Ranking
公开(公告)号：US20210064999A1
公开(公告)日：2021-03-04
申请号：US17003112
申请日：2020-08-26
Applicant: NEC Laboratories America, Inc.
Inventor： Yanchi Liu , Wei Cheng , Bo Zong , LuAn Tang , Haifeng Chen , Denghui Zhang
Abstract: Methods and systems for allocating network resources responsive to network traffic include modeling spatial correlations between fine spatial granularity traffic and coarse spatial granularity traffic for different sites and regions to determine spatial feature vectors for one or more sites in a network. Temporal correlations at a fine spatial granularity are modeled across multiple temporal scales, based on the spatial feature vectors. Temporal correlations at a coarse spatial granularity are modeled across multiple temporal scales, based on the spatial feature vectors. A traffic flow prediction is determined for the one or more sites in the network, based on the temporal correlations at the fine spatial granularity and the temporal correlations at the coarse spatial granularity. Network resources are provisioned at the one or more sites in accordance with the traffic flow prediction.
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公开(公告)号：US10929765B2
公开(公告)日：2021-02-23
申请号：US15678751
申请日：2017-08-16
Applicant: NEC Laboratories America, Inc.
Inventor： Biplob Debnath , Hui Zhang , Jianwu Xu , Nipun Arora , Guofei Jiang , Bo Zong
Abstract: A computer-implemented method for automatically analyzing log contents received via a network and detecting content-level anomalies is presented. The computer-implemented method includes building a statistical model based on contents of a set of training logs and detecting, based on the set of training logs, content-level anomalies for a set of testing logs. The method further includes maintaining an index and metadata, generating attributes for fields, editing model capability to incorporate user domain knowledge, detecting anomalies using field attributes, and improving anomaly quality by using user feedback.
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公开(公告)号：US20210049414A1
公开(公告)日：2021-02-18
申请号：US16936600
申请日：2020-07-23
Applicant: NEC Laboratories America, Inc.
Inventor： Bo Zong , Cheng Zheng , Haifeng Chen
Abstract: A method for employing a differentiable ranking based graph sparsification (DRGS) network to use supervision signals from downstream tasks to guide graph sparsification is presented. The method includes, in a training phase, generating node representations by neighborhood aggregation operators, generating sparsified subgraphs by top-k neighbor sampling from a learned neighborhood ranking distribution, feeding the sparsified subgraphs to a task, generating a prediction, and collecting a prediction error to update parameters in the generating and feeding steps to minimize an error, and, in a testing phase, generating node representations by neighborhood aggregation operators related to testing data, generating sparsified subgraphs by top-k neighbor sampling from a learned neighborhood ranking distribution related to the testing data, feeding the sparsified subgraphs related to the testing data to a task, and outputting prediction results to a visualization device.
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公开(公告)号：US10909115B2
公开(公告)日：2021-02-02
申请号：US16203008
申请日：2018-11-28
Applicant: NEC Laboratories America, Inc.
Inventor： Bo Zong , Jianwu Xu , Haifeng Chen
IPC: G06F7/00 , G06F16/2453 , G06F16/2458 , G06F16/2455 , G06F16/9038 , G06F16/17 , G06F16/14 , G06F11/08 , G06K9/62
Abstract: Systems and methods for system event searching based on heterogeneous logs are provided. A system can include a processor device operatively coupled to a memory device wherein the processor device is configured to mine a variety of log patterns from various of heterogeneous logs to obtain known-event log patterns and unknown-event log patterns, as well as to build a weighted vector representation of the log patterns. The processor device is also configured to evaluate a similarity between the vector representation of the unknown-event and known-event log patterns, identify a known event that is most similar to an unknown event to troubleshoot system faults based on past actions for similar events to improve an operation of a computer system.
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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.
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