IP Library Granted Patent US 12,500,870
Granted Patent B2
US 12,500,870 · App. 18/336,873 · Granted Dec 16, 2025

Network action classification and analysis using widely distributed and selectively attributed sensor nodes and cloud-based processing

Inventors: Jason Crabtree (Vienna, VA); Richard Kelley (Woodbridge, VA)
Assignee: QOMPLX LLC
H04L63/0428H04L9/3236H04L9/3239H04L63/0807H04L63/0815H04L63/1425H04L63/1433H04L63/145
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Quick Facts
Patent No.
US 12,500,870
App. No.
18/336,873
Filed
Jun 16, 2023
Granted
Dec 16, 2025
Kind
B2
Art Unit
2493
USPC
713/180
Abstract

A system for network traffic classification using distributed sensor nodes is provided, comprising a plurality of network traffic sensors each configured to monitor visible network traffic, analyze the monitored traffic to identify patterns, communicate with other network sensors to correlate their respective traffic data, produce a threat landscape based on the correlated traffic data, identify a potential cybersecurity threat based on the threat landscape, and export the analyzed traffic and threat landscape for use by external systems.

Claims (19)

1 . A system for network traffic classification using distributed sensor nodes, comprising:

a plurality of network traffic sensors each comprising a plurality of programming instructions stored in a memory of, and operating on a processor of, a respective computing device, wherein each plurality of programmable instructions, when operating on the processor, cause the respective computing device to:

monitor visible network traffic at a geographically distributed network location;

analyze the monitored traffic to identify a plurality of patterns, wherein the analysis comprises analysis of a plurality of traffic sources and destinations;

communicate with at least one other of the plurality of network traffic sensors to correlate the identified plurality of patterns across multiple geographic points of observation;

produce a threat landscape, wherein the threat landscape comprises multi-source classification of identified traffic patterns indicative of potential cybersecurity threats;

provide the threat landscape to an edge server or edge network device for local threat response and policy enforcement; and

export the analyzed traffic data and the threat landscape to at least one external system for integration with security decision-making systems.

2 . The system of claim 1 , wherein the network traffic sensor is configured to operate a network-accessible software service.

3 . The system of claim 2 , wherein a potential cybersecurity threat is identified based on traffic involving the network-accessible software service.

4 . A method for network traffic classification using distributed sensor nodes, comprising the steps of:

monitoring visible network traffic at a geographically distributed network location;

analyzing the monitored traffic to identify a plurality of patterns, wherein the analysis comprises analysis of a plurality of traffic sources and destinations;

communicating with at least one other of the plurality of network traffic sensors to correlate the identified plurality of patterns across multiple geographic points of observation;

producing a threat landscape, wherein the threat landscape comprises multi-source classification of identified traffic patterns indicative of potential cybersecurity threats;

providing the threat landscape to an edge server or edge network device for local threat response and policy enforcement; and

exporting the analyzed traffic data and the threat landscape to at least one external system for integration with security decision-making systems.

5 . The method of claim 4 , wherein the network traffic sensor is configured to operate a network-accessible software service.

6 . The method of claim 5 , wherein a potential cybersecurity threat is identified based on traffic involving the network-accessible software service.

Assignments (6)
CHANGE OF ADDRESS Recorded Oct 1, 2024
From: QOMPLX LLC
To: QOMPLX LLC
Reel/Frame 069083/0279 →
CORRECTIVE ASSIGNMENT TO CORRECT THE CONVEYING PARTY DATA NAME: RICHARD KELLEY PREVIOUSLY RECORDED AT REEL: 064412 FRAME: 0639. ASSIGNOR(S) HEREBY CONFIRMS THE ASSIGNMENT. Recorded Jan 18, 2024
From: CRABTREE, JASON; KELLEY, RICHARD
To: QOMPLX, INC.
Reel/Frame 066343/0738 →
CHANGE OF NAME Recorded Sep 27, 2023
From: QPX LLC
To: QOMPLX LLC
Reel/Frame 065036/0449 →
CORRECTIVE ASSIGNMENT TO CORRECT THE RECEIVING PARTY PREVIOUSLY RECORDED AT REEL: 064674 FRAME: 0408. ASSIGNOR(S) HEREBY CONFIRMS THE ASSIGNMENT. Recorded Sep 20, 2023
From: QOMPLX, INC.
To: QPX LLC
Reel/Frame 064966/0863 →
PATENT ASSIGNMENT AGREEMENT TO ASSET PURCHASE AGREEMENT Recorded Aug 23, 2023
From: QOMPLX, INC.
To: QPX, LLC.
Reel/Frame 064674/0407 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Jul 28, 2023
From: CRABTREE, JASON; KELLY, RICHARD
To: QOMPLX, INC.
Reel/Frame 064412/0639 →
Continuity (19)
Continuation In Part 18297500 · Apr 7, 2023
Continuation In Part 18169203 · Feb 14, 2023
Continuation In Part 17245162 · Apr 30, 2021
Continuation 15837845 · Dec 11, 2017
Continuation In Part 15825350 · Nov 29, 2017
Continuation In Part 15725274 · Oct 4, 2017
Continuation In Part 15655113 · Jul 20, 2017
Continuation In Part 15616427 · Jun 7, 2017
Continuation In Part 15237625 · Aug 15, 2016
Continuation In Part 15206195 · Jul 8, 2016
Continuation In Part 15186453 · Jun 18, 2016
Continuation In Part 15166158 · May 26, 2016
Continuation In Part 15141752 · Apr 28, 2016
Continuation In Part 15091563 · Apr 5, 2016
Continuation In Part 14986536 · Dec 31, 2015
Continuation In Part 14925974 · Oct 28, 2015
Continuation In Part 14925974 · Oct 28, 2015
Provisional Application 62596105 · Dec 7, 2017
Related Publication 20230362142A1 · Nov 9, 2023
References Cited (53)
US 5669000A · Jessen et al. · 1997 [cited by applicant]
US 6256544B1 · Weissinger · 2001 [cited by applicant]
US 6477572B1 · Elderton et al. · 2002 [cited by applicant]
US 7260844B1 · Tidwell · 2007 [cited by examiner]
US 8042180B2 · Gassoway · 2011 [cited by examiner]
US 8949960B2 · Berkman et al. · 2015 [cited by applicant]
US 9137131B1 · Sarukkai et al. · 2015 [cited by applicant]
US 9516053B1 · Muddu · 2016 [cited by examiner]
US 10154066B1 · Madhukar · 2018 [cited by examiner]
US 10462112B1 · Makmel et al. · 2019 [cited by applicant]
US 10560510B2 · Li · 2020 [cited by examiner]
US 11005824B2 · Crabtree et al. · 2021 [cited by applicant]
US 11165804B2 · Herley · 2021 [cited by applicant]
US 11265346B2 · Xiao et al. · 2022 [cited by applicant]
US 20030041254A1 · Challener et al. · 2003 [cited by applicant]
US 20030145225A1 · Bruton et al. · 2003 [cited by applicant]
US 20070036314A1 · Kloberdans et al. · 2007 [cited by applicant]
US 20070150744A1 · Cheng et al. · 2007 [cited by applicant]
US 20090182672A1 · Doyle · 2009 [cited by applicant]
US 20090199002A1 · Erickson · 2009 [cited by applicant]
US 20090222562A1 · Liu et al. · 2009 [cited by applicant]
US 20110087888A1 · Rennie · 2011 [cited by applicant]
US 20120266244A1 · Green et al. · 2012 [cited by applicant]
US 20120297483A1 · Boot · 2012 [cited by examiner]
US 20130061313A1 · Cullimore · 2013 [cited by examiner]
US 20130291107A1 · Marck · 2013 [cited by examiner]
US 20140156806A1 · Karpistsenko et al. · 2014 [cited by applicant]
US 20140279762A1 · Xaypanya et al. · 2014 [cited by applicant]
US 20140380466A1 · Schultz · 2014 [cited by examiner]
US 20150149979A1 · Talby et al. · 2015 [cited by applicant]
US 20150169294A1 · Brock et al. · 2015 [cited by applicant]
US 20150195192A1 · Vasseur et al. · 2015 [cited by applicant]
US 20150281225A1 · Schoen et al. · 2015 [cited by applicant]
US 20150317481A1 · Gardner et al. · 2015 [cited by applicant]
US 20150379424A1 · Dirac et al. · 2015 [cited by applicant]
US 20160028758A1 · Ellis et al. · 2016 [cited by applicant]
US 20160072845A1 · Chiviendacz et al. · 2016 [cited by applicant]
US 20160078361A1 · Brueckner et al. · 2016 [cited by applicant]
US 20160162690A1 · Reith · 2016 [cited by examiner]
US 20160275123A1 · Lin et al. · 2016 [cited by applicant]
US 20160364307A1 · Garg et al. · 2016 [cited by applicant]
US 20170019678A1 · Kim et al. · 2017 [cited by applicant]
US 20170126712A1 · Crabtree et al. · 2017 [cited by applicant]
US 20170139763A1 · Ellwein · 2017 [cited by applicant]
US 20170149802A1 · Huang et al. · 2017 [cited by applicant]
US 20170193110A1 · Crabtree et al. · 2017 [cited by applicant]
US 20170322959A1 · Tidwell et al. · 2017 [cited by applicant]
US 20170323089A1 · Duggal et al. · 2017 [cited by applicant]
US 20180300930A1 · Kennedy et al. · 2018 [cited by applicant]
US 20190082305A1 · Proctor · 2019 [cited by applicant]
US 20200235935A1 · Cerna, Jr. · 2020 [cited by applicant]
WO 2014159150A1 · 2014 [cited by applicant]
WO 2017075543A1 · 2017 [cited by applicant]