IP Library Granted Patent US 10,594,709
Granted Patent B2
US 10,594,709 · App. 16/384,574 · Granted Mar 17, 2020

Adaptive network monitoring with tuneable elastic granularity

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.
H04L63/1416G06N20/00H04L41/0681H04L43/08H04L63/1408H04L43/0894
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Quick Facts
Patent No.
US 10,594,709
App. No.
16/384,574
Filed
Apr 15, 2019
Granted
Mar 17, 2020
Kind
B2
Art Unit
2437
USPC
726/23
Abstract

Embodiments are directed to monitoring network traffic using network computers. Monitoring triggers associated with one or more conditions and one or more actions may be provided. A monitoring engine may monitor information that is associated with network traffic associated with networks based on an inspection detail level. The monitoring engine may compare the monitored information to the conditions associated with the monitoring triggers. The monitoring engine may activate one or more monitoring triggers based on a result of the comparison. The monitoring engine may modify the inspection detail level based on the actions associated with the activated monitoring triggers to increase the amount of the information monitored by the monitoring engine. An analysis engine may provide analysis of the network traffic based on the monitored information.

Claims (63)

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

passively monitoring information that is associated with network traffic associated with one or more networks;

in response to a determination that one or more conditions associated with activating one or more triggers for the monitored information has occurred, performing actions, including:

ranking a priority for each activated trigger, wherein an allocation of one or more of compute, data storage, or network resources for each activated trigger is based on its rank;

modifying a deep packet level of inspection based on an available amount of the one or more of compute, data storage or network resources allocated to each activated trigger, wherein the modification initiates or stops the deep packet level of inspection for the monitored information; and

employing available resources to perform the deep packet level of inspection on packets that were communicated in the network traffic during the occurrence of the one or more conditions; and

providing analysis of the network traffic based on the monitored information and the deep packet level of inspection for the packets.

2. The method of claim 1 , wherein the passive monitoring information, further comprises:

in response to a non-occurrence of the one or more conditions, performing another level of inspection of the packets that is less comprehensive than the deep packet level of inspection.

3. The method of claim 1 , wherein the determination that one or more conditions have occurred, further comprises:

employing the deep packet level of inspection to additionally monitor information associated with the network traffic; and

in response to the additionally monitored information, activating one or more other triggers that provide associated alerts to a user.

4. The method of claim 1 , wherein the passively monitored information further comprises:

providing one or more metrics associated with the network traffic, and wherein the one or more metrics include collecting information regarding one or more different layers of a same network flow.

5. The method of claim 1 , wherein the performing of the deep packet level of inspection on packets that were communicated in the network traffic, further comprises providing one or more metrics for network traffic communicated by one or more entities on the one or more networks.

6. The method of claim 1 , further comprising:

providing one or more agents that perform one or more actions, including:

capturing one or more portions of the packets that were communicated in the network traffic during the occurrence of the one or more conditions; or

capturing one or more portions of one or more network flows associated with the occurrence of the one or more conditions.

7. The method of claim 1 , wherein employing the available resources, further comprises:

providing a resource budget that is associated with the one or more networks and the one or more activated triggers, wherein at least a portion of the resource budget is allocated as available resources based on a resource cost that is associated with each activated trigger.

8. 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 actions, comprising:

passively monitoring information that is associated with network traffic associated with one or more networks;

in response to a determination that one or more conditions associated with activating one or more triggers for the monitored information has occurred, performing actions, including:

ranking a priority for each activated trigger, wherein an allocation of one or more of compute, data storage, or network resources for each activated trigger is based on its rank;

modifying a deep packet level of inspection based on an available amount of the one or more of compute, data storage or network resources allocated to each activated trigger, wherein the modification initiates or stops the deep packet level of inspection for the monitored information; and

employing available resources to perform the deep packet level of inspection on packets that were communicated in the network traffic during the occurrence of the one or more conditions; and

providing analysis of the network traffic based on the monitored information and the deep packet level of inspection for the packets.

9. The media of claim 8 , wherein the passive monitoring information, further comprises:

in response to a non-occurrence of the one or more conditions, performing another level of inspection of the packets that is less comprehensive than the deep packet level of inspection.

10. The media of claim 8 , wherein the determination that one or more conditions have occurred, further comprises:

employing the deep packet level of inspection to additionally monitor information associated with the network traffic; and

in response to the additionally monitored information, activating one or more other triggers that provide associated alerts to a user.

11. The media of claim 8 , wherein the passively monitored information further comprises:

providing one or more metrics associated with the network traffic, and wherein the one or more metrics include collecting information regarding one or more different layers of a same network flow.

12. The media of claim 8 , wherein the performing of the deep packet level of inspection on packets that were communicated in the network traffic, further comprises providing one or more metrics for network traffic communicated by one or more entities on the one or more networks.

13. The media of claim 8 , further comprising:

providing one or more agents that perform one or more actions, including:

capturing one or more portions of the packets that were communicated in the network traffic during the occurrence of the one or more conditions; or

capturing one or more portions of one or more network flows associated with the occurrence of the one or more conditions.

14. The media of claim 8 , wherein employing the available resources, further comprises:

providing a resource budget that is associated with the one or more networks and the one or more activated triggers, wherein at least a portion of the resource budget is allocated as available resources based on a resource cost that is associated with each activated trigger.

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

a memory that stores at least instructions; and

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

passively monitoring information that is associated with network traffic associated with one or more networks;

in response to a determination that one or more conditions associated with activating one or more triggers for the monitored information has occurred, performing actions, including:

ranking a priority for each activated trigger, wherein an allocation of one or more of compute, data storage, or network resources for each activated trigger is based on its rank;

modifying a deep packet level of inspection based on an available amount of the one or more of compute, data storage or network resources allocated to each activated trigger, wherein the modification initiates or stops the deep packet level of inspection for the monitored information; and

employing available resources to perform the deep packet level of inspection on packets that were communicated in the network traffic during the occurrence of the one or more conditions; and

providing analysis of the network traffic based on the monitored information and the deep packet level of inspection for the packets.

16. The network computer of claim 15 , wherein the passive monitoring information, further comprises:

in response to a non-occurrence of the one or more conditions, performing another level of inspection of the packets that is less comprehensive than the deep packet level of inspection.

17. The network computer of claim 15 , wherein the determination that one or more conditions have occurred, further comprises:

employing the deep packet level of inspection to additionally monitor information associated with the network traffic; and

in response to the additionally monitored information, activating one or more other triggers that provide associated alerts to a user.

18. The network computer of claim 15 , wherein the passively monitored information further comprises:

providing one or more metrics associated with the network traffic, and wherein the one or more metrics include collecting information regarding one or more different layers of a same network flow.

19. The network computer of claim 15 , wherein the performing of the deep packet level of inspection on packets that were communicated in the network traffic, further comprises providing one or more metrics for network traffic communicated by one or more entities on the one or more networks.

20. The network computer of claim 15 , further comprising:

providing one or more agents that perform one or more actions, including:

capturing one or more portions of the packets that were communicated in the network traffic during the occurrence of the one or more conditions; or

capturing one or more portions of one or more network flows associated the occurrence of the one or more conditions.

Assignments (6)
RELEASE OF SECURITY INTEREST Recorded Jul 28, 2021
From: SILICON VALLEY BANK
To: EXTRAHOP NETWORKS, INC.
Reel/Frame 057010/0001 →
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 →
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 Apr 15, 2019
From: WU, XUE JUN; BRAUN, NICHOLAS JORDAN; DEAGUERO, JOEL BENJAMIN; MONTAGUE, MICHAEL KERBER KRAUSE; KHANAL, BHUSHAN PRASAD
To: EXTRAHOP NETWORKS, INC.
Reel/Frame 048888/0354 →
Continuity (2)
Continuation 15891311 · Feb 7, 2018
Related Publication 20190245873A1 · Aug 8, 2019
Cited By (7)
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