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    ANOMALY CLASSIFICATION WITH ATTENDANT WORD ENRICHMENT
    2.
    发明申请
    ANOMALY CLASSIFICATION WITH ATTENDANT WORD ENRICHMENT 有权

    公开(公告)号：US20240370656A1

    公开(公告)日：2024-11-07

    申请号：US18743282

    申请日：2024-06-14

    Applicant: Cisco Technology, Inc.

    Inventor： Dmitri Goloubev ,  Nassim Benoussaid ,  Volodymyr Iashyn ,  Borys Viacheslavovych Berlog ,  Carlos M. Pignataro

    IPC: G06F40/30 ,  G06F16/28 ,  G06F16/35 ,  G06F40/279 ,  G06N20/00

    Abstract: A method includes associating anomalous first text, from a first unstructured data set, with a first classification; processing the first unstructured data set using at least one of ML or AI to identify a second text that is in close context to the first text, and adding the second text to a text list associated with the first classification; enriching the text list by processing the second text to generate a third text, and adding the third text to the text list to produce an enriched text list and such that the third text is also associated with the first classification; matching the text in the enriched text list to text in a second unstructured data set; and classifying the text in the second unstructured data set as having the first classification when the text in the second unstructured data set matches text in the enriched text list.

    SOCIAL MEDIA AI MITIGATION AND MASKING
    4.
    发明申请
    SOCIAL MEDIA AI MITIGATION AND MASKING 有权

    公开(公告)号：US20220164826A1

    公开(公告)日：2022-05-26

    申请号：US17105031

    申请日：2020-11-25

    Applicant: Cisco Technology, Inc.

    Inventor： M. David Hanes ,  Gonzalo Salgueiro ,  Sebastian Jeuk ,  Robert E. Barton ,  Nassim Benoussaid

    IPC: G06Q30/02 ,  G06Q50/00 ,  G06N20/00

    Abstract: In one embodiment, a device obtains content data provided by a social media platform to a user of the social media platform. The social media platform selects the content data for the user based on a behavioral model of the user. The device maintains an artificial intelligence-based model that models associations between the content data and interaction data indicative of interactions between the user and the social media platform. The device selects, using the artificial intelligence-based model, an obfuscation action to lower an accuracy of the behavioral model of the user, based on one or more configuration parameters set by the user. The device initiates performance of the obfuscation action.

    MODEL STRUCTURE EXTRACTION FOR ANALYZING UNSTRUCTURED TEXT DATA
    5.
    发明申请
    MODEL STRUCTURE EXTRACTION FOR ANALYZING UNSTRUCTURED TEXT DATA 有权

    公开(公告)号：US20210027167A1

    公开(公告)日：2021-01-28

    申请号：US16522871

    申请日：2019-07-26

    Applicant: Cisco Technology, Inc.

    Inventor： Dmitry Goloubew ,  Nassim Benoussaid ,  Borys Viacheslavovych Berlog ,  Carlos M. Pignataro

    IPC: G06N3/08 ,  G06F16/21

    Abstract: In one embodiment, a device obtains an output of a machine learning-based anomaly detector for unstructured text. The output of the anomaly detector includes a sequence of text analyzed by the detector and an indication that a portion of the sequence of text was flagged by the detector as an anomaly. The device extracts a context for the anomaly as an n-gram of portions of the sequence of text surrounding the anomaly. The device identifies a structure of the anomaly by identifying anchor portions of the extracted context. The device generates, based on the identified structure, an expression that represents the structure of the anomaly within the unstructured text.

    PROXY MODEL WITH DELAYED RE-VALIDATION
    6.
    发明申请
    PROXY MODEL WITH DELAYED RE-VALIDATION 有权

    公开(公告)号：US20230066759A1

    公开(公告)日：2023-03-02

    申请号：US17463738

    申请日：2021-09-01

    Applicant: Cisco Technology, Inc.

    Inventor： Nassim Benoussaid ,  David John Zacks ,  Zizhen Gao ,  Carlos M. Pignataro ,  Dmitry Goloubev

    IPC: G06N20/00

    Abstract: Techniques are provided for segmentation of data points after a dimension reduction. A proxy model is then trained based on results of the segmentation. The proxy model provides low latency high throughput labeling of additional data points, without the need to reduce dimensions of the additional data points. A second segmentation is performed with results of the second segmentation compared to that of the first segmentation. When results of the comparison meet certain criterion, configuration parameters of the segmentation are modified. For example, in some embodiments, a user interface is provided that displays shapley values indicating a mapping from the high dimension data to the segmented data. Input is then received that modifies the configuration parameters.

    SPATIO-TEMPORAL EVENT WEIGHT ESTIMATION FOR NETWORK-LEVEL AND TOPOLOGY-LEVEL REPRESENTATIONS
    8.
    发明申请
    SPATIO-TEMPORAL EVENT WEIGHT ESTIMATION FOR NETWORK-LEVEL AND TOPOLOGY-LEVEL REPRESENTATIONS 有权

    公开(公告)号：US20220086050A1

    公开(公告)日：2022-03-17

    申请号：US17079728

    申请日：2020-10-26

    Applicant: Cisco Technology, Inc.

    Inventor： Dmitri Goloubev ,  Nassim Benoussaid ,  Luc De Ghein ,  Carlos M. Pignataro ,  Hugo M. Latapie

    IPC: H04L12/24 ,  H04L29/06 ,  H04L12/715

    Abstract: Presented herein are techniques to analyze network anomaly signals based on both a spatial component and a temporal component. A method includes identifying a plurality of factors that trigger a first anomaly signal by a first network node and a second anomaly signal by a second network node in a network comprising a plurality of network nodes, determining that the first network node is adjacent to the second network node in the plurality of network nodes, calculating an anomaly severity score for the first network node based on a number of co-occurring factors from among the plurality of factors that trigger both the first anomaly signal and the second anomaly signal, and adjusting the anomaly severity score for the first network node based on a value of a prior anomaly severity score for the first network node.

    ANOMALY CLASSIFICATION WITH ATTENDANT WORD ENRICHMENT
    9.
    发明申请
    ANOMALY CLASSIFICATION WITH ATTENDANT WORD ENRICHMENT 有权

    公开(公告)号：US20210342543A1

    公开(公告)日：2021-11-04

    申请号：US16914899

    申请日：2020-06-29

    Applicant: Cisco Technology, Inc.

    Inventor： Dmitri Goloubev ,  Nassim Benoussaid ,  Volodymyr Iashyn ,  Borys Viacheslavovych Berlog ,  Carlos M. Pignataro

    IPC: G06F40/30 ,  G06F16/35 ,  G06F16/28 ,  G06N20/00 ,  G06F40/279

    Abstract: A method includes associating anomalous first text, from a first unstructured data set, with a first classification; processing the first unstructured data set using at least one of ML or AI to identify a second text that is in close context to the first text, and adding the second text to a text list associated with the first classification; enriching the text list by processing the second text to generate a third text, and adding the third text to the text list to produce an enriched text list and such that the third text is also associated with the first classification; matching the text in the enriched text list to text in a second unstructured data set; and classifying the text in the second unstructured data set as having the first classification when the text in the second unstructured data set matches text in the enriched text list.

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