IP Library Granted Patent US 10,038,611
Granted Patent B1
US 10,038,611 · App. 15/892,327 · Granted Jul 31, 2018

Personalization of alerts based on network monitoring

Inventors: Xue Jun Wu (Seattle, WA); Nicholas Jordan Braun (Seattle, WA); Joel Benjamin Deaguero (Seattle, WA); Michael Kerber Krause Montague (Lake Forest Park, WA); Bhushan Prasad Khanal (Seattle, WA)
Assignee: ExtraHop Networks, Inc.
H04L43/08G06N5/04H04L41/06H04L41/0681H04L41/14H04L41/145H04L41/22H04L43/045G06F17/30867
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Quick Facts
Patent No.
US 10,038,611
App. No.
15/892,327
Filed
Feb 8, 2018
Granted
Jul 31, 2018
Kind
B1
Art Unit
2457
USPC
709/224
Abstract

Embodiments are directed to monitoring network traffic using network computers. A monitoring engine may monitor network traffic associated with a plurality of entities in a network to provide metrics. A device relation model may be provided based on the plurality of entities, the network traffic, and the metrics. Interest information for a user may be provided based on one or more properties associated with the user. An inference engine may associate each entity in the plurality of entities with an interest score based on the interest information, the device relation model, and the metrics. An alert engine may generate a plurality of alerts associated with the plurality of entities based on the metrics. Some of the alerts may be provided to the user based on ranked interest scores associated with the entities.

Claims (101)

1. A method for monitoring network traffic using one or more network computers, wherein execution of instructions by the one or more network computers perform the method comprising:

instantiating a monitoring engine to perform actions, including:

monitoring network traffic associated with a plurality of entities in one or more networks to provide one or more metrics;

providing a device relation model based on the plurality of entities, the network traffic, and the one or more metrics; and

providing interest information for a user based on one or more properties associated with the user;

instantiating an inference engine to perform actions including associating each entity in the plurality of entities with an interest score that is further associated with a level of interest to the user, wherein the level of interest is based on the interest information, the device relation model, and the one or more metrics; and

instantiating an alert engine to perform actions, including:

generating a plurality of alerts associated with the plurality of entities based on the one or more metrics; and

providing one or more alerts to the user from the plurality of alerts based on one or more ranked interest scores associated with one or more entities.

2. The method of claim 1 , wherein the inference engine performs further actions, comprising:

monitoring an amount of interactions by the user with the plurality of entities; and

increasing the interest score associated with each of the plurality of entities based on the monitored amount of user interactions.

3. The method of claim 1 , wherein the inference engine performs further actions, comprising:

providing a list of entities to the user based on the interest information and the device relation model; and

modifying the interest score associated with one or more listed entities based on input by the user.

4. The method of claim 1 , wherein the inference engine performs further actions, comprising:

traversing the device relation model based on the interest information;

providing one or more other entities based on the traversal; and

modifying the interest score that is associated with the one or more other entities based on the traversal.

5. The method of claim 1 , wherein the actions of the inference engine further comprises, modifying the interest score of an entity based on one or more of applications shared by the entity and one or more other entities, dependencies shared by the entity and the one or more other entities, or activities of other users.

6. The method of claim 1 , wherein the actions of the inference engine further comprise, modifying the interest score that is associated a portion of the plurality of entities based on one or more heuristics, wherein the one or more heuristics compare the one or more properties associated with the user to one or more user roles.

7. The method of claim 1 , wherein the actions of the inference engine further comprise, modifying the interest score that is associated a portion of the plurality of entities based on a distance between entities in the device relation model.

8. The method of claim 1 , wherein the actions of the inference engine further comprise, modifying the interest score that is associated a portion of the plurality of entities based on one or more properties that are associated with the portion of the plurality of the entities.

9. A processor readable non-transitory storage media that includes instructions for monitoring network traffic using one or more network monitoring computers, wherein execution of the instructions by the one or more network computers perform the method comprising:

instantiating a monitoring engine to perform actions, including:

monitoring network traffic associated with a plurality of entities in one or more networks to provide one or more metrics;

providing a device relation model based on the plurality of entities, the network traffic, and the one or more metrics; and

providing interest information for a user based on one or more properties associated with the user;

instantiating an inference engine to perform actions including associating each entity in the plurality of entities with an interest score that is further associated with a level of interest to the user, wherein the level of interest is based on the interest information, the device relation model, and the one or more metrics; and

instantiating an alert engine to perform actions, including:

generating a plurality of alerts associated with the plurality of entities based on the one or more metrics; and

providing one or more alerts to the user from the plurality of alerts based on one or more ranked interest scores associated with one or more entities.

10. The media of claim 9 , wherein the inference engine performs further actions, comprising:

monitoring an amount of interactions by the user with the plurality of entities; and

increasing the interest score associated with each of the plurality of entities based on the monitored amount of user interactions.

11. The media of claim 9 , wherein the inference engine performs further actions, comprising:

providing a list of entities to the user based on the interest information and the device relation model; and

modifying the interest score associated with one or more listed entities based on input by the user.

12. The media of claim 9 , wherein the inference engine performs further actions, comprising:

traversing the device relation model based on the interest information;

providing one or more other entities based on the traversal; and

modifying the interest score that is associated with the one or more other entities based on the traversal.

13. The media of claim 9 , wherein the actions of the inference engine further comprises, modifying the interest score of an entity based on one or more of applications shared by the entity and one or more other entities, dependencies shared by the entity and the one or more other entities, or activities of other users.

14. The media of claim 9 , wherein the actions of the inference engine further comprise, modifying the interest score that is associated a portion of the plurality of entities based on one or more heuristics, wherein the one or more heuristics compare the one or more properties associated with the user to one or more user roles.

15. The media of claim 9 , wherein the actions of the inference engine further comprise, modifying the interest score that is associated a portion of the plurality of entities based on a distance between entities in the device relation model.

16. A system for monitoring network traffic in a network:

one or more network computers, comprising:

a transceiver that communicates over the network;

a memory that stores at least instructions; and

one or more processors that execute instructions that perform actions, including:

instantiating a monitoring engine to perform actions, including:

monitoring network traffic associated with a plurality of entities in one or more networks to provide one or more metrics;

providing a device relation model based on the plurality of entities, the network traffic, and the one or more metrics; and

providing interest information for a user based on one or more properties associated with the user;

instantiating an inference engine to perform actions including associating each entity in the plurality of entities with an interest score that is further associated with a level of interest to the user, wherein the level of interest is based on the interest information, the device relation model, and the one or more metrics; and

instantiating an alert engine to perform actions, including:

generating a plurality of alerts associated with the plurality of entities based on the one or more metrics; and

providing one or more alerts to the user from the plurality of alerts based on one or more ranked interest scores associated with one or more entities, and

one or more client computers, comprising:

a transceiver that communicates over the network;

a memory that stores at least instructions; and

one or more processors that execute instructions that perform actions, including:

providing one or more portions of the network traffic.

17. The system of claim 16 , wherein the inference engine performs further actions, comprising:

monitoring an amount of interactions by the user with the plurality of entities; and

increasing the interest score associated with each of the plurality of entities based on the monitored amount of user interactions.

18. The system of claim 16 , wherein the inference engine performs further actions, comprising:

providing a list of entities to the user based on the interest information and the device relation model; and

modifying the interest score associated with one or more listed entities based on input by the user.

19. The system of claim 16 , wherein the inference engine performs further actions, comprising:

traversing the device relation model based on the interest information;

providing one or more other entities based on the traversal; and

modifying the interest score that is associated with the one or more other entities based on the traversal.

20. The system of claim 16 , wherein the actions of the inference engine further comprises, modifying the interest score of an entity based on one or more of applications shared by the entity and one or more other entities, dependencies shared by the entity and the one or more other entities, or activities of other users.

21. The system of claim 16 , wherein the actions of the inference engine further comprise, modifying the interest score that is associated a portion of the plurality of entities based on one or more heuristics, wherein the one or more heuristics compare the one or more properties associated with the user to one or more user roles.

22. The system of claim 16 , wherein the actions of the inference engine further comprise, modifying the interest score that is associated a portion of the plurality of entities based on a distance between entities in the device relation model.

23. The system of claim 16 , wherein the actions of the inference engine further comprise, modifying the interest score that is associated a portion of the plurality of entities based on one or more properties that are associated with the portion of the plurality of the entities.

24. A network computer for monitoring communication over a network between two or more computers, comprising:

a transceiver that communicates over the network;

a memory that stores at least instructions; and

one or more processors that execute instructions that perform actions, including:

instantiating a monitoring engine to perform actions, including:

monitoring network traffic associated with a plurality of entities in one or more networks to provide one or more metrics;

providing a device relation model based on the plurality of entities, the network traffic, and the one or more metrics; and

providing interest information for a user based on one or more properties associated with the user;

instantiating an inference engine to perform actions including associating each entity in the plurality of entities with an interest score that is further associated with a level of interest to the user, wherein the level of interest is based on the interest information, the device relation model, and the one or more metrics; and

instantiating an alert engine to perform actions, including:

generating a plurality of alerts associated with the plurality of entities based on the one or more metrics; and

providing one or more alerts to the user from the plurality of alerts based on one or more ranked interest scores associated with one or more entities.

25. The network computer of claim 24 , wherein the inference engine performs further actions, comprising:

monitoring an amount of interactions by the user with the plurality of entities; and

increasing the interest score associated with each of the plurality of entities based on the monitored amount of user interactions.

26. The network computer of claim 24 , wherein the inference engine performs further actions, comprising: providing a list of entities to the user based on the interest information and the device relation model; and

modifying the interest score associated with one or more listed entities based on input by the user.

27. The network computer of claim 24 , wherein the inference engine performs further actions, comprising:

traversing the device relation model based on the interest information;

providing one or more other entities based on the traversal; and

modifying the interest score that is associated with the one or more other entities based on the traversal.

28. The network computer of claim 24 , wherein the actions of the inference engine further comprises, modifying the interest score of an entity based on one or more of applications shared by the entity and one or more other entities, dependencies shared by the entity and the one or more other entities, or activities of other users.

29. The network computer of claim 24 , wherein the actions of the inference engine further comprise, modifying the interest score that is associated a portion of the plurality of entities based on one or more heuristics, wherein the one or more heuristics compare the one or more properties associated with the user to one or more user roles.

30. The network computer of claim 24 , wherein the actions of the inference engine further comprise, modifying the interest score that is associated a portion of the plurality of entities based on a distance between entities in the device relation model.

Assignments (6)
SECURITY INTEREST Recorded Jul 27, 2021
From: EXTRAHOP NETWORKS, INC.
To: SIXTH STREET SPECIALTY LENDING, INC., AS THE COLLATERAL AGENT
Reel/Frame 056998/0590 →
RELEASE OF SECURITY INTEREST Recorded Jul 22, 2021
From: SILICON VALLEY BANK
To: EXTRAHOP NETWORKS, INC.
Reel/Frame 056967/0488 →
RELEASE OF SECURITY INTEREST Recorded Jul 22, 2021
From: SILICON VALLEY BANK
To: EXTRAHOP NETWORKS, INC.
Reel/Frame 056967/0530 →
SECURITY INTEREST Recorded Sep 11, 2020
From: EXTRAHOP NETWORKS, INC.
To: SILICON VALLEY BANK
Reel/Frame 053756/0739 →
SECURITY INTEREST Recorded Sep 11, 2020
From: EXTRAHOP NETWORKS, INC.
To: SILICON VALLEY BANK, AS AGENT
Reel/Frame 053756/0774 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Feb 8, 2018
From: WU, XUE JUN; BRAUN, NICHOLAS JORDAN; DEAGUERO, JOEL BENJAMIN; MONTAGUE, MICHAEL KERBER KRAUSE; KHANAL, BHUSHAN PRASAD
To: EXTRAHOP NETWORKS, INC.
Reel/Frame 044876/0342 →
Cited By (9)
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