公开(公告)号：US11818155B2

公开(公告)日：2023-11-14

申请号：US17568399

申请日：2022-01-04

申请人： Intellective Ai, Inc.

发明人： Wesley Kenneth Cobb ,  Ming-Jung Seow ,  Curtis Edward Cole, Jr. ,  Cody Shay Falcon ,  Benjamin A. Konosky ,  Charles Richard Morgan ,  Aaron Poffenberger ,  Thong Toan Nguyen

IPC分类号： H04L9/40 ,  G06N20/00 ,  G06F40/30 ,  G06F40/226 ,  G06F40/242 ,  G06F40/289 ,  G06F40/40 ,  G06F40/247 ,  G06F40/253 ,  G06F40/284

CPC分类号： H04L63/1425 ,  G06F40/226 ,  G06F40/242 ,  G06F40/289 ,  G06F40/30 ,  G06N20/00 ,  H04L63/1408 ,  G06F40/247 ,  G06F40/253 ,  G06F40/284 ,  G06F40/40

摘要： Embodiments presented herein describe a method for processing streams of data of one or more networked computer systems. According to one embodiment of the present disclosure, an ordered stream of normalized vectors corresponding to information security data obtained from one or more sensors monitoring a computer network is received. A neuro-linguistic model of the information security data is generated by clustering the ordered stream of vectors and assigning a letter to each cluster, outputting an ordered sequence of letters based on a mapping of the ordered stream of normalized vectors to the clusters, building a dictionary of words from of the ordered output of letters, outputting an ordered stream of words based on the ordered output of letters, and generating a plurality of phrases based on the ordered output of words.

公开(公告)号：US11017168B2

公开(公告)日：2021-05-25

申请号：US16523500

申请日：2019-07-26

申请人： Intellective Ai, Inc.

发明人： Gang Xu ,  Ming-Jung Seow ,  Tao Yang ,  Wesley Kenneth Cobb

IPC分类号： G06F40/30 ,  G06N20/00 ,  G06F40/242 ,  G06N5/04 ,  G06F40/289

摘要： Techniques are disclosed for building a dictionary of words from combinations of symbols generated based on input data. A neuro-linguistic behavior recognition system includes a neuro-linguistic module that generates a linguistic model that describes data input from a source (e.g., video data, SCADA data, etc.). To generate words for the linguistic model, a lexical analyzer component in the neuro-linguistic module receives a stream of symbols, each symbol generated based on an ordered stream of normalized vectors generated from input data. The lexical analyzer component determines words from combinations of the symbols based on a hierarchical learning model having one or more levels. Each level indicates a length of the words to be identified at that level. Statistics are evaluated for the words identified at each level. The lexical analyzer component identifies one or more of the words having statistical significance.

公开(公告)号：US10735446B2

公开(公告)日：2020-08-04

申请号：US15978150

申请日：2018-05-13

申请人： Intellective Ai, Inc.

发明人： Wesley Kenneth Cobb ,  Ming-Jung Seow ,  Curtis Edward Cole ,  Cody Shay Falcon ,  Benjamin A. Konosky ,  Charles Richard Morgan ,  Aaron Poffenberger ,  Thong Toan Nguyen

IPC分类号： H04L29/06 ,  G06N20/00 ,  G06F40/30 ,  G06F40/226 ,  G06F40/242 ,  G06F40/289 ,  G06F40/40 ,  G06F40/247 ,  G06F40/253 ,  G06F40/284

摘要： Embodiments presented herein describe a method for processing streams of data of one or more networked computer systems. According to one embodiment of the present disclosure, an ordered stream of normalized vectors corresponding to information security data obtained from one or more sensors monitoring a computer network is received. A neuro-linguistic model of the information security data is generated by clustering the ordered stream of vectors and assigning a letter to each cluster, outputting an ordered sequence of letters based on a mapping of the ordered stream of normalized vectors to the clusters, building a dictionary of words from of the ordered output of letters, outputting an ordered stream of words based on the ordered output of letters, and generating a plurality of phrases based on the ordered output of words.

公开(公告)号：US12051210B2

公开(公告)日：2024-07-30

申请号：US17509837

申请日：2021-10-25

申请人： Intellective Ai, Inc.

发明人： Gang Xu ,  Ming-Jung Seow ,  Tao Yang ,  Wesley Kenneth Cobb

IPC分类号： G06K9/00 ,  G06N20/00 ,  G06T7/20 ,  G06V10/75 ,  G06V20/52 ,  G06V10/62 ,  G06V20/40 ,  G08B13/196

CPC分类号： G06T7/20 ,  G06N20/00 ,  G06V10/758 ,  G06V20/52 ,  G06V10/62 ,  G06V20/44 ,  G08B13/19613

摘要： Techniques are disclosed for analyzing and learning behavior in an acquired stream of video frames. In one embodiment, a trajectory analyzer clusters trajectories of objects depicted in video frames and builds a trajectory model including the trajectory clusters, a prior probability of assigning a trajectory to each cluster, and an intra-cluster probability distribution indicating the probability that a trajectory mapping to each cluster is least various distances away from the cluster. Given a new trajectory, a score indicating how unusual the trajectory is may be computed based on the product of the probability of the trajectory mapping to a particular cluster and the intra-cluster probability of the trajectory being a computed distance from the cluster. The distance used to match the trajectory to the cluster and determine intra-cluster probability is computed using a parallel Needleman-Wunsch algorithm, with cells in antidiagonals of a matrix and connected sub-matrices being computed in parallel.

公开(公告)号：US11875784B2

公开(公告)日：2024-01-16

申请号：US17107383

申请日：2020-11-30

申请人： Intellective Ai, Inc.

发明人： Gang Xu ,  Tao Yang ,  Ming-Jung Seow

IPC分类号： G10L15/16 ,  G10L15/197 ,  G06N20/00 ,  G06F40/237 ,  G06V20/52 ,  G06V40/20

CPC分类号： G10L15/16 ,  G06F40/237 ,  G06N20/00 ,  G06V20/52 ,  G06V40/20 ,  G10L15/197

摘要： Techniques are disclosed to optimize feature selection in generating betas for a feature dictionary of a neuro-linguistic Cognitive AI System. A machine learning engine receives a sample vector of input data to be analyzed by the neuro-linguistic Cognitive AI System. The neuro-linguistic Cognitive AI System is configured to generate multiple betas for each of a plurality of sensors. The machine learning engine identifies a sensor specified in the sample vector and selects optimization parameters for generating betas based on the identified sensor.

公开(公告)号：US11847413B2

公开(公告)日：2023-12-19

申请号：US17328606

申请日：2021-05-24

申请人： Intellective Ai, Inc.

发明人： Gang Xu ,  Ming-Jung Seow ,  Tao Yang ,  Wesley Kenneth Cobb

IPC分类号： G06F40/30 ,  G06N20/00 ,  G06F40/242 ,  G06N5/045 ,  G06F40/289

CPC分类号： G06F40/242 ,  G06F40/289 ,  G06N5/045 ,  G06N20/00

摘要： Techniques are disclosed for building a dictionary of words from combinations of symbols generated based on input data. A neuro-linguistic behavior recognition system includes a neuro-linguistic module that generates a linguistic model that describes data input from a source (e.g., video data, SCADA data, etc.). To generate words for the linguistic model, a lexical analyzer component in the neuro-linguistic module receives a stream of symbols, each symbol generated based on an ordered stream of normalized vectors generated from input data. The lexical analyzer component determines words from combinations of the symbols based on a hierarchical learning model having one or more levels. Each level indicates a length of the words to be identified at that level. Statistics are evaluated for the words identified at each level. The lexical analyzer component identifies one or more of the words having statistical significance.

公开(公告)号：US11699278B2

公开(公告)日：2023-07-11

申请号：US17397297

申请日：2021-08-09

申请人： Intellective Ai, Inc.

发明人： Ming-Jung Seow ,  Gang Xu ,  Tao Yang ,  Wesley K. Cobb

IPC分类号： G06V10/32 ,  G06F16/23 ,  G06F16/28 ,  G06V30/262 ,  H01B1/02 ,  G06F18/23 ,  G06F18/28 ,  G06F18/2137 ,  G06N7/01 ,  G06V30/19 ,  G06V10/762

CPC分类号： G06V10/32 ,  G06F18/2137 ,  G06F18/23 ,  G06F18/28 ,  G06N7/01 ,  G06V10/762 ,  G06V30/1914 ,  G06V30/19127 ,  G06V30/268 ,  H01B1/02

摘要： Techniques are disclosed for generating a sequence of symbols based on input data for a neuro-linguistic model. The model may be used by a behavior recognition system to analyze the input data. A mapper component of a neuro-linguistic module in the behavior recognition system receives one or more normalized vectors generated from the input data. The mapper component generates one or more clusters based on a statistical distribution of the normalized vectors. The mapper component evaluates statistics and identifies statistically relevant clusters. The mapper component assigns a distinct symbol to each of the identified clusters.

公开(公告)号：US10909322B1

公开(公告)日：2021-02-02

申请号：US15881945

申请日：2018-01-29

申请人： Intellective Ai, Inc.

发明人： Ming-Jung Seow ,  Gang Xu ,  Tao Yang ,  Wesley Kenneth Cobb

IPC分类号： G06F40/30 ,  G08B21/18 ,  G06F40/211 ,  G06F40/242

摘要： Techniques are disclosed for generating anomaly scores for a neuro-linguistic model of input data obtained from one or more sources. According to one embodiment, generating anomaly scores includes receiving a stream of symbols generated from an ordered stream of normalized vectors generated from input data received from one or more sensor devices during a first time period. Upon receiving the stream of symbols, generating a set of words based on an occurrence of groups of symbols from the stream of symbols, determining a number of previous occurrences of a first word of the set of words, determining a number of previous occurrences of words of a same length as the first word, and determining a first anomaly score based on the number of previous occurrences of the first word and the number of previous occurrences of words of the same length as the first word.

公开(公告)号：US10657434B2

公开(公告)日：2020-05-19

申请号：US15091209

申请日：2016-04-05

申请人： Intellective Ai, Inc.

发明人： Ming-Jung Seow ,  Gang Xu ,  Tao Yang ,  Wesley Kenneth Cobb

IPC分类号： G06N3/02

摘要： Techniques are disclosed for generating an anomaly score for a neuro-linguistic model of input data obtained from one or more sources. According to one embodiment, generating an anomaly score comprises receiving a score indicating how often a characteristic is observed in the input data. Upon receiving the score, comparing the score with an unusual score model to determine an unusualness score and comparing the unusualness score with an anomaly score model based on one or more unusual score models to generate the anomaly score indicating an overall unusualness for the input data.

公开(公告)号：US12032909B2

公开(公告)日：2024-07-09

申请号：US17479331

申请日：2021-09-20

申请人： Intellective Ai, Inc.

发明人： Ming-Jung Seow ,  Gang Xu ,  Tao Yang ,  Wesley Kenneth Cobb

IPC分类号： G06F40/30 ,  G06F40/242 ,  G06F40/284 ,  G06F40/40 ,  G06N20/00

CPC分类号： G06F40/284 ,  G06F40/242 ,  G06F40/40

摘要： Techniques are disclosed for generating a syntax for a neuro-linguistic model of input data obtained from one or more sources. A stream of words of a dictionary built from a sequence of symbols are received. The symbols are generated from an ordered stream of normalized vectors generated from input data. Statistics for combinations of words co-occurring in the stream are evaluated. The statistics includes a frequency upon which the combinations of words co-occur. A model of combinations of words based on the evaluated statistics is updated. The model identifies statistically relevant words. A connected graph is generated. Each node in the connected graph represents one of the words in the stream. Edges connecting the nodes represent a probabilistic relationship between words in the stream. Phrases are identified based on the connected graph.