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Patent Agency Ranking
公开(公告)号：US10824535B1
公开(公告)日：2020-11-03
申请号：US16266447
申请日：2019-02-04
Inventor： Rajiv Shah , Shannon Morrison , Jeremy Cunningham , Taylor Smith , Sripriya Sundararaman , Jing Wan , Jeffrey Hevrin , Ronald Duehr , Brad Sliz , Lucas Allen
Abstract: A computer-implemented method for determining features of a dataset that are indicative of anomalous behavior of one or more computers in a large group of computers comprises (1) receiving log files including a plurality of entries of data regarding connections between a plurality of computers belonging to an organization and a plurality of websites outside the organization, each entry being associated with the actions of one computer, (2) executing a time series decomposition algorithm on a portion of the features of the data to generate a first list of features, (3) implementing a plurality of traffic dispersion graphs to generate a second list of features, and (4) implementing an autoencoder and a random forest regressor to generate a third list of features.
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公开(公告)号：US11321214B1
公开(公告)日：2022-05-03
申请号：US17068821
申请日：2020-10-12
Inventor： Rajiv Shah , Shannon Morrison , Jeremy Cunningham , Taylor Smith , Sripriya Sundararaman , Jing Wan , Jeffrey Hevrin , Ronald Duehr , Brad Sliz , Lucas Allen
Abstract: A computer-implemented method for determining features of a dataset that are indicative of anomalous behavior of one or more computers in a large group of computers comprises (1) receiving log files including a plurality of entries of data regarding connections between a plurality of computers belonging to an organization and a plurality of websites outside the organization, each entry being associated with the actions of one computer, (2) executing a time series decomposition algorithm on a portion of the features of the data to generate a first list of features, (3) implementing a plurality of traffic dispersion graphs to generate a second list of features, and (4) implementing an autoencoder and a random forest regressor to generate a third list of features.
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公开(公告)号：US10652257B1
公开(公告)日：2020-05-12
申请号：US15643716
申请日：2017-07-07
Inventor： Rajiv Shah , Shannon Morrison , Jeremy Cunningham , Taylor Smith , Sripriya Sundararaman , Jing Wan , Jeffrey Hevrin , Ronald Duehr , Brad Sliz , Lucas Allen
IPC: H04L29/06
Abstract: A computer-implemented method for detecting anomalous behavior of one or more computers in a large group of computers comprises (1) receiving log files including a plurality of entries of data regarding connections between a plurality of computers belonging to an organization and a plurality of websites outside the organization, each entry being associated with the actions of one computer, (2) applying a first plurality of algorithms to determine features of the data which may contribute to anomalous behavior of the computers, and (3) applying a second plurality of algorithms to determine which computers are behaving anomalously based upon the features.
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公开(公告)号：US10248533B1
公开(公告)日：2019-04-02
申请号：US15643757
申请日：2017-07-07
Inventor： Rajiv Shah , Shannon Morrison , Jeremy Cunningham , Taylor Smith , Sripriya Sundararaman , Jing Wan , Jeffrey Hevrin , Ronald Duehr , Brad Sliz , Lucas Allen
Abstract: A computer-implemented method for determining features of a dataset that are indicative of anomalous behavior of one or more computers in a large group of computers comprises (1) receiving log files including a plurality of entries of data regarding connections between a plurality of computers belonging to an organization and a plurality of websites outside the organization, each entry being associated with the actions of one computer, (2) executing a time series decomposition algorithm on a portion of the features of the data to generate a first list of features, (3) implementing a plurality of traffic dispersion graphs to generate a second list of features, and (4) implementing an autoencoder and a random forest regressor to generate a third list of features.
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公开(公告)号：US11310253B1
公开(公告)日：2022-04-19
申请号：US16842351
申请日：2020-04-07
Inventor： Rajiv Shah , Shannon Morrison , Jeremy Cunningham , Taylor Smith , Sripriya Sundararaman , Jing Wan , Jeffrey Hevrin , Ronald Duehr , Brad Sliz , Lucas Allen
IPC: H04L29/06
Abstract: A computer-implemented method for detecting anomalous behavior of one or more computers in a large group of computers comprises (1) receiving log files including a plurality of entries of data regarding connections between a plurality of computers belonging to an organization and a plurality of websites outside the organization, each entry being associated with the actions of one computer, (2) applying a first plurality of algorithms to determine features of the data which may contribute to anomalous behavior of the computers, and (3) applying a second plurality of algorithms to determine which computers are behaving anomalously based upon the features.
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