-
公开(公告)号：US11240259B2
公开(公告)日：2022-02-01
申请号：US16508398
申请日：2019-07-11
Applicant: Cisco Technology, Inc.
Inventor： Jean-Philippe Vasseur , Sébastien Gay , Grégory Mermoud , Pierre-André Savalle , Alexandre Honoré , Fabien Flacher
Abstract: In one embodiment, a networking device at an edge of a network generates a first set of feature vectors using information regarding one or more characteristics of host devices in the network. The networking device forms the host devices into device clusters dynamically based on the first set of feature vectors. The networking device generates a second set of feature vectors using information regarding traffic associated with the device clusters. The networking device models interactions between the device clusters using a plurality of anomaly detection models that are based on the second set of feature vectors.
-
Patent Agency Ranking
公开(公告)号：US10701092B2
公开(公告)日：2020-06-30
申请号：US15364440
申请日：2016-11-30
Applicant: Cisco Technology, Inc.
Inventor： Laurent Sartran , Sébastien Gay , Jean-Philippe Vasseur , Grégory Mermoud
IPC: H04L29/06
Abstract: In one embodiment, a device in a network obtains characteristic data regarding one or more traffic flows in the network. The device incrementally estimates an amount of noise associated with a machine learning feature using bootstrapping. The machine learning feature is derived from the sampled characteristic data. The device applies a filter to the estimated amount of noise associated with the machine learning feature, to determine a value for the machine learning feature. The device identifies a network anomaly that exists in the network by using the determined value for the machine learning feature as input to a machine learning-based anomaly detector. The device causes performance of an anomaly mitigation action based on the identified network anomaly.
-
13.发明申请公开(公告)号：US20190342321A1
公开(公告)日：2019-11-07
申请号：US16517748
申请日：2019-07-22
Applicant: Cisco Technology, Inc.
Inventor： Laurent Sartran , Sébastien Gay , Pierre-André Savalle , Grégory Mermoud , Jean-Philippe Vasseur
Abstract: In one embodiment, a device in a network receives traffic records indicative of network traffic between different sets of host address pairs. The device identifies one or more address grouping constraints for the sets of host address pairs. The device determines address groups for the host addresses in the sets of host address pairs based on the one or more address grouping constraints. The device provides an indication of the address groups to an anomaly detector.
-
公开(公告)号：US20190334941A1
公开(公告)日：2019-10-31
申请号：US16508398
申请日：2019-07-11
Applicant: Cisco Technology, Inc.
Inventor： Jean-Philippe Vasseur , Sébastien Gay , Grégory Mermoud , Pierre-André Savalle , Alexandre Honoré , Fabien Flacher
Abstract: In one embodiment, a networking device at an edge of a network generates a first set of feature vectors using information regarding one or more characteristics of host devices in the network. The networking device forms the host devices into device clusters dynamically based on the first set of feature vectors. The networking device generates a second set of feature vectors using information regarding traffic associated with the device clusters. The networking device models interactions between the device clusters using a plurality of anomaly detection models that are based on the second set of feature vectors.
-
公开(公告)号：US10218729B2
公开(公告)日：2019-02-26
申请号：US15205122
申请日：2016-07-08
Applicant: Cisco Technology, Inc.
Inventor： Sébastien Gay , Laurent Sartran , Jean-Philippe Vasseur
Abstract: In one embodiment, a device in a network receives sets of traffic flow features from an unsupervised machine learning-based anomaly detector. The sets of traffic flow features are associated with anomaly scores determined by the anomaly detector. The device ranks the sets of traffic flow features based in part on their anomaly scores. The device applies a genetic programming approach to the ranked sets of traffic flow features to generate new sets of traffic flow features. The genetic programming approach uses a fitness function that is based in part on the rankings of the sets of traffic flow features. The device specializes the anomaly detector to emphasize a particular type of anomaly using the new sets of traffic flow features.
-
公开(公告)号：US20170279698A1
公开(公告)日：2017-09-28
申请号：US15188175
申请日：2016-06-21
Applicant: Cisco Technology, Inc.
Inventor： Laurent Sartran , Pierre-André Savalle , Jean-Philippe Vasseur , Grégory Mermoud , Javier Cruz Mota , Sébastien Gay
IPC: H04L12/26
CPC classification number: H04L43/0876 , H04L41/142 , H04L41/147 , H04L41/16 , H04L43/028 , H04L43/0823 , H04L43/16
Abstract: In one embodiment, a device in a network determines cluster assignments that assign traffic data regarding traffic in the network to activity level clusters based on one or more measures of traffic activity in the traffic data. The device uses the cluster assignments to predict seasonal activity for a particular subset of the traffic in the network. The device determines an activity level for new traffic data regarding the particular subset of traffic in the network. The device detects a network anomaly by comparing the activity level for the new traffic data to the predicted seasonal activity.
-
-
-
-
-
Search Results
16
records
(took 0.026 seconds)
