公开(公告)号：US20190236511A1

公开(公告)日：2019-08-01

申请号：US16163546

申请日：2018-10-17

申请人： Clari Inc.

发明人： Xin XU ,  Chunyue DU ,  Xincheng MA ,  Kaiyue WU ,  Venkat RANGAN

IPC分类号： G06Q10/06 ,  G06F17/30

CPC分类号： G06Q10/06375 ,  G06F9/485 ,  G06F16/903 ,  G06N3/0445 ,  G06N20/20 ,  G06Q10/063112 ,  G06Q10/063118 ,  G06Q10/0633 ,  G06Q10/0637 ,  G06Q10/0639

摘要： In an embodiment, described herein is a system and method for creating a suggested task set to meet a target value. A cloud server, in response to receiving a request specifying a target value, retrieves completed task sets from a database. Each completed task set includes a same set of task categories. The cloud server derives a number of ratios from the retrieved completed task sets, including a composition ratio and a conversion rate for each task category, and an addition ratio for the number of completed task sets. Based on the derived ratios and the specified target value, the cloud server constructs the suggested task set, and displays in real-time the suggested task set together with current values for the task categories. The cloud server alerts users of a discrepancy between a current value and the corresponding suggested value for a task category when the discrepancy reaches a predetermined level.

公开(公告)号：US20190236273A1

公开(公告)日：2019-08-01

申请号：US16257749

申请日：2019-01-25

申请人： Sophos Limited

发明人： Joshua Daniel SAXE ,  Ethan M. RUDD ,  Richard HARANG

IPC分类号： G06F21/56 ,  G06N20/20 ,  G06N3/04 ,  G06K9/62

CPC分类号： G06F21/563 ,  G06F21/56 ,  G06F21/562 ,  G06K9/6256 ,  G06K9/6267 ,  G06N3/04 ,  G06N3/0454 ,  G06N5/003 ,  G06N20/20

摘要： An apparatus for detecting malicious files includes a memory and a processor communicatively coupled to the memory. The processor receives multiple potentially malicious files. A first potentially malicious file has a first file format, and a second potentially malicious file has a second file format different than the first file format. The processor extracts a first set of strings from the first potentially malicious file, and extracts a second set of strings from the second potentially malicious file. First and second feature vectors are defined based on lengths of each string from the associated set of strings. The processor provides the first feature vector as an input to a machine learning model to produce a maliciousness classification of the first potentially malicious file, and provides the second feature vector as an input to the machine learning model to produce a maliciousness classification of the second potentially malicious file.

公开(公告)号：US20190220758A1

公开(公告)日：2019-07-18

申请号：US16363639

申请日：2019-03-25

申请人： Huawei Technologies Co., Ltd.

发明人： Roman TALYANSKY ,  Zach MELAMED ,  Natan PETERFREUND ,  Zuguang WU

IPC分类号： G06N5/04 ,  G06N20/20 ,  G06K9/62 ,  G06F17/18

CPC分类号： G06N5/043 ,  G06F11/1482 ,  G06F17/18 ,  G06K9/6256 ,  G06K9/6267 ,  G06N20/00 ,  G06N20/20

摘要： A distributed system for training a classifier is provided. The system comprises machine learning (ML) workers and a parameter server (PS). The PS is configured for parallel processing to provide the model to each of the ML workers, receive model updates from each of the ML workers, and iteratively update the model using each model update. The PS contains gradient datasets associated with a respective ML worker, for storing a model-update-identification (delta-M-ID) indicative of the computed model update and the respective model update, a global dataset that stores, the delta-M-ID, an identification of the ML worker (ML-worker-ID) that computed the model update, and a model version that marks a new model in PS that is computed from merging the model update with a previous model in PS; and a model download dataset that stores the ML-worker-ID and the model version of each transmitted model.

公开(公告)号：US20190220710A1

公开(公告)日：2019-07-18

申请号：US16362186

申请日：2019-03-22

申请人： ZhongAn Information Technology Service Co., Ltd.

发明人： Wenpeng SONG ,  Xiong SHEN

IPC分类号： G06K9/62 ,  G06N20/20

CPC分类号： G06K9/6282 ,  G06F16/9535 ,  G06K9/6265 ,  G06N20/20

摘要： A data processing method includes: generating at least one incremental decision tree according to incremental data; predicting the incremental data based on multiple model decision trees in a classification model and the at least one incremental decision tree to obtain prediction results; and updating the classification model according to the prediction results. In the data processing method according to an embodiment of the present invention, by generating the at least one incremental decision tree according to the incremental data, and then predicting the incremental data based on the model decision trees in the classification model and the at least one incremental decision tree, and updating the classification model according to the prediction results, a self-adaptive update of the classification model is achieved, and a manual intervention during a business cycle of the classification model is not needed, so that the cost is saved greatly.

公开(公告)号：US20190207960A1

公开(公告)日：2019-07-04

申请号：US16236976

申请日：2018-12-31

申请人： DataVisor, Inc.

发明人： Kuanyu Chu ,  Hongyu Cui ,  Arthur Meng ,  Zhong Wu ,  Yunfeng Xi ,  Yinglian Xie ,  Ting-Fang Yen ,  Fang Yu

IPC分类号： H04L29/06 ,  G06N20/20 ,  G06F17/18 ,  G06K9/62 ,  G06F16/901

CPC分类号： H04L63/1416 ,  G06F16/9024 ,  G06F17/18 ,  G06K9/6215 ,  G06K9/6218 ,  G06N20/20 ,  H04L63/1433

摘要： Methods, systems, and apparatus, including computer programs encoded on computer storage media, for detecting network attacks. One of the methods includes obtaining input data associated with a plurality of accounts associated with a particular entity; extracting features from the input data; performing unsupervised attack ring detection using the extracted features, wherein the unsupervised attack ring detection identifies suspicious clusters of accounts that have strong similarity or correlations in the high dimensional feature space; and generating an output for the detected attack rings.

公开(公告)号：US20190206391A1

公开(公告)日：2019-07-04

申请号：US16235396

申请日：2018-12-28

申请人： SYNTIANT

发明人： Kurt F. Busch ,  Jeremiah H. Holleman, III ,  Pieter Vorenkamp ,  Stephen W. Bailey

IPC分类号： G10L15/16 ,  G10L15/28 ,  G10L15/22 ,  G06N3/08 ,  G06N20/20

CPC分类号： G10L15/16 ,  G06N3/08 ,  G06N20/20 ,  G10L15/22 ,  G10L15/28 ,  G10L2015/088 ,  G10L2015/223

摘要： Provided herein is an integrated circuit including, in some embodiments, a special-purpose host processor, a neuromorphic co-processor, and a communications interface between the host processor and the co-processor configured to transmit information therebetween. The special-purpose host processor is operable as a stand-alone host processor. The neuromorphic co-processor includes an artificial neural network. The co-processor is configured to enhance special-purpose processing of the host processor through the artificial neural network. In such embodiments, the host processor is a keyword identifier processor configured to transmit one or more detected words to the co-processor over the communications interface. The co-processor is configured to transmit recognized words, or other sounds, to the host processor.

公开(公告)号：US20190138743A1

公开(公告)日：2019-05-09

申请号：US16238437

申请日：2019-01-02

申请人： LeapYear Technologies, Inc.

发明人： Ishaan Nerurkar ,  Christopher Hockenbrocht ,  Liam Damewood

IPC分类号： G06F21/62 ,  G06F16/2455 ,  G06F16/248 ,  H04L29/06 ,  G06F16/25 ,  G06N20/00 ,  G06F16/2453 ,  G06N5/00

CPC分类号： G06F21/6227 ,  G06F16/2453 ,  G06F16/24547 ,  G06F16/2455 ,  G06F16/248 ,  G06F16/25 ,  G06F21/6218 ,  G06F21/6245 ,  G06N5/003 ,  G06N20/00 ,  G06N20/10 ,  G06N20/20 ,  H04L63/105

摘要： A hardware database privacy device is communicatively coupled to a private database system. The hardware database privacy device receives a request from a client device to perform a query of the private database system and identifies a level of differential privacy corresponding to the request. The identified level of differential privacy includes privacy parameters (ε,δ) indicating the degree of information released about the private database system. The hardware database privacy device identifies a set of operations to be performed on the set of data that corresponds to the requested query. After the set of data is accessed, the set of operations is modified based on the identified level of differential privacy such that a performance of the modified set of operations produces a result set that is (ε,δ)-differentially private.

公开(公告)号：US20190122077A1

公开(公告)日：2019-04-25

申请号：US16085989

申请日：2017-03-15

申请人： IMRA EUROPE S.A.S.

发明人： Dzmitry TSISHKOU ,  Rémy BENDAHAN

IPC分类号： G06K9/62 ,  G06N3/08 ,  G06N3/04 ,  G06N20/20 ,  G06K9/46 ,  G06K9/00 ,  G05D1/02 ,  G05D1/00

CPC分类号： G06K9/6257 ,  G05D1/0088 ,  G05D1/0231 ,  G05D2201/0213 ,  G06K9/00791 ,  G06K9/4676 ,  G06K9/623 ,  G06K9/6259 ,  G06K9/6277 ,  G06K9/629 ,  G06N3/0454 ,  G06N3/08 ,  G06N3/084 ,  G06N20/20

摘要： Some embodiments are directed to a method to reinforce deep neural network learning capacity to classify rare cases, which includes the steps of training a first deep neural network used to classify generic cases of original data into specified labels; localizing discriminative class-specific features within the original data processed through the first deep neural network and mapping the discriminative class-specific features as spatial-probabilistic labels; training a second-deep neural network used to classify rare cases of the original data into the spatial-probabilistic labels; and training a combined deep neural network used to classify both generic and rare cases of the original data into primary combined specified and spatial-probabilistic labels.

公开(公告)号：US20190102277A1

公开(公告)日：2019-04-04

申请号：US15725250

申请日：2017-10-04

申请人： BlackBerry Limited

发明人： Andrew Walenstein ,  Andrew James MALTON ,  Jong Chun PARK ,  Hanyang Hu

IPC分类号： G06F11/36 ,  G06N99/00

CPC分类号： G06F11/362 ,  G06F11/36 ,  G06N5/003 ,  G06N20/00 ,  G06N20/20

摘要： A method for classifying warning messages generated by software developer tools includes receiving a first data set. The first data set includes a first plurality of data entries, where each data entry is associated with a warning message generated based on a first set of software codes, includes indications for a plurality of features, and is associated with one of a plurality of class labels. A second data set is generated by sampling the first data set. Based on the second data set, at least one feature is selected from the plurality of features. A third data set is generated by filtering the second data set with the selected at least one feature. A machine learning classifier is determined based on the third data set. The machine learning classifier is used to classify a second warning message generated based on a second set of software codes to one of the plurality of class labels.

公开(公告)号：US20180367428A1

公开(公告)日：2018-12-20

申请号：US15626412

申请日：2017-06-19

申请人： Cisco Technology, Inc.

发明人： Andrea Di Pietro ,  Grégory Mermoud ,  Jean-Philippe Vasseur ,  Sukrit Dasgupta

IPC分类号： H04L12/26 ,  H04L29/06 ,  G06F17/30

CPC分类号： H04L43/0817 ,  G06F16/24578 ,  G06N3/0472 ,  G06N3/08 ,  G06N5/003 ,  G06N5/04 ,  G06N7/005 ,  G06N20/10 ,  G06N20/20 ,  H04L41/0213 ,  H04L41/0816 ,  H04L41/145 ,  H04L41/147 ,  H04L43/08 ,  H04L43/10 ,  H04L63/1408 ,  H04L63/1433

摘要： In one embodiment, a device receives health status data indicative of a health status of a data source in a network that provides collected telemetry data from the network for analysis by a machine learning-based network analyzer. The device maintains a performance model for the data source that models the health of the data source. The device computes a trustworthiness index for the telemetry data provided by the data source based on the received health status data and the performance model for the data source. The device adjusts, based on the computed trustworthiness index for the telemetry data provided by the data source, one or more parameters used by the machine learning-based network analyzer to analyze the telemetry data provided by the data source.