Extreme Networks, Inc.

Jeffrey W Haskell

Richard W Graham

Markus Nispel

Ernie Eaton

Donagh S Horgan

Patrick A Bosa

David L Kjendal

Giacomo Bernardi

Disclosed herein are system, method, and computer program product embodiments for providing an anomaly detection system. Some aspects of this disclosure include a method for detecting anomaly in a network device. The method includes determining one or more similarity values between a flow vector corresponding to a flow associated with the network device and one or more flow clusters associated with the network device. The method further includes determining a maximum similarity value as a maximum of the one or more similarity values and comparing the maximum similarity value to a threshold. The method also includes, in response to the maximum similarity value being equal to or greater than the threshold, updating a flow cluster associated with the maximum similarity value. The method also includes, in response to the maximum similarity measure being less than the threshold, detecting the anomaly in the network device.

Online anomaly detection of vector embeddings

A function is provided in a network system for the dynamic mirroring of network traffic for a variety of purposes including the identification of characteristics of the traffic. Multiple criteria are established for when, what and where to mirror the traffic. The criteria include what frames of traffic to mirror, what portions of the selected frames to mirror, one or more portals through which to minor the selected frames, a destination for the mirroring and the establishment of a mirror in a device to carry out the mirroring. The criteria may also include when to stop the mirroring. The mirroring instructions can be changed based on the detection of a triggering event, such as authentication, device type or status, ownership of an attached function attached to the device, flow status, but not limited to that. The function may be established in one or more devices of the network.

Device and related method for dynamic traffic mirroring

A function is provided in a network system for the dynamic mirroring of network traffic for a variety of purposes including the identification of characteristics of the traffic. Multiple criteria are established for when, what and where to mirror the traffic. The criteria include what frames of traffic to mirror, what portions of the selected frames to mirror, one or more portals through which to mirror the selected frames, a destination for the mirroring and the establishment of a mirror in a device to carry out the mirroring. The criteria may also include when to stop the mirroring. The mirroring instructions can be changed based on the detection of a triggering event, such as authentication, device type or status, ownership of an attached function attached to the device, flow status, but not limited to that. The function may be established in one or more devices of the network.

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New Boston, NH, United States of America

Jeffrey W Haskell