IP Library › Granted Patent US 12,381,902
Granted Patent B2
US 12,381,902 · App. 18/226,161 · Granted Aug 5, 2025

Pattern match-based detection in IOT security

Inventors: Jun Du (Cupertino, CA); Mei Wang (Saratoga, CA); Hector Daniel Regalado (Santa Clara, CA); Jianhong Xia (Santa Clara, CA)
Assignee: Palo Alto Networks, Inc.
H04L63/1425G06N20/00H04L63/20
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Quick Facts
Patent No.
US 12,381,902
App. No.
18/226,161
Filed
Jul 25, 2023
Granted
Aug 5, 2025
Kind
B2
Art Unit
2435
USPC
726/23
Abstract

Techniques for providing Internet of Things (IoT) security are disclosed. An applicable system includes profiling IoT devices to limit the number of network signatures applicable to the IoT devices and performing pattern matching using a pattern that is appropriate for the profile of a given IoT device.

Claims (49)

1. A method of detecting undesirable behavior of an Internet-of-Things (IoT) device, comprising:

associating a first subset of patterns of a superset of patterns with a first IoT device profile, wherein the first IoT device profile belongs to a set comprising a plurality of IoT device profiles;

attributing the first IoT device profile to a first IoT device as a first provisional profile and attributing a second provisional profile to the first IoT device;

detecting first IoT device events, the first IoT device events including one or more network sessions of the first IoT device;

generating an activity data structure from the first IoT device events and from other events, including by enriching at least one event by associating enrichment data with the at least one event, wherein the enrichment data comprises at least one of: (1) another event, or (2) information appended to the at least one event, wherein the generated activity data structure comprises a labeled collection of events, wherein at least one of the other events comprises a non-network event, and wherein a first event is treated differently for the first provisional profile than the second provisional profile;

determining an activity of the first IoT device based on the activity data structure;

applying the first subset of patterns to the activity of the first IoT device; and

generating an alert when the application of the first subset of patterns to the activity of the first IoT device is indicative of undesirable behavior for a device to which the first IoT device profile is attributed.

2. The method of claim 1 , wherein the first IoT device profile is attributed to the first IoT device prior to deployment of the first IoT device.

3. The method of claim 1 , wherein the first IoT device profile is attributed to the first IoT device after deployment of the first IoT device.

4. The method of claim 1 , wherein the first IoT device profile is attributed to the first IoT device after deployment of the first IoT device, and the first IoT device profile is a default IoT device profile that is dynamically modified using available data.

5. The method of claim 1 , wherein the first IoT device events are detected using passive monitoring.

6. The method of claim 1 , wherein the first IoT device events are detected using packet headers in messages sent to or from the first IoT device.

7. The method of claim 1 , wherein the first IoT device events are aggregated to form one or more composite first IoT device events using machine learning.

8. The method of claim 1 , wherein the first IoT device events are aggregated to form one or more composite first IoT device events using a device implemented as part of a local area network (LAN) that includes the first IoT device.

9. The method of claim 1 , wherein the first IoT device does not have a history of previously exhibited undesirable behavior, and the undesirable behavior includes anomalous behavior of the first IoT device.

10. The method of claim 1 , wherein the first IoT device has a history of previously exhibited undesirable behavior, and the undesirable behavior includes normal behavior of the first IoT device.

11. The method of claim 1 , wherein a plurality of discrete events are aggregated to form one or more composite events using machine learning.

12. The method of claim 11 , wherein the one or more composite events are formed using common factor aggregation.

13. The method of claim 12 , wherein a common factor used in the common factor aggregation includes a device profile common to a plurality of devices.

14. The method of claim 12 , wherein a common factor used in the common factor aggregation includes an operating system vendor common to a plurality of devices.

15. The method of claim 12 , wherein a common factor used in the common factor aggregation includes an operating system version common to a plurality of devices.

16. The method of claim 12 , wherein a common factor used in the common factor aggregation includes use of an application common to a plurality of devices.

17. The method of claim 12 , wherein a common factor used in the common factor aggregation includes communication via a particular subnetwork common to a plurality of devices.

18. A system comprising:

a processor configured to:

associate a first subset of patterns of a superset of patterns with a first IoT device profile, wherein the first IoT device profile belongs to a set comprising a plurality of IoT device profiles;

attribute the first IoT device profile to a first IoT device as a first provisional profile and attribute a second provisional profile to the first IoT device;

detect first IoT device events, the first IoT device events including one or more network sessions of the first IoT device;

generate an activity data structure from the first IoT device events and from other events, including by enriching at least one event by associating enrichment data with the at least one event, wherein the enrichment data comprises at least one of: (1) another event, or (2) information appended to the at least one event, wherein the generated activity data structure comprises a labeled collection of events, wherein at least one of the other events comprises a non-network event, and wherein a first event is treated differently for the first provisional profile than the second provisional profile;

determine an activity of the first IoT device based on the activity data structure;

apply the first subset of patterns to the activity of the first IoT device; and

generate an alert when the application of the first subset of patterns to the activity of the first IoT device is indicative of undesirable behavior for a device to which the first IoT device profile is attributed.

19. The system of claim 18 , wherein the first IOT device profile is attributed to the first IoT device prior to deployment of the first IOT device.

20. The system of claim 18 , wherein the first IoT device profile is attributed to the first IOT device after deployment of the first IOT device.

21. The system of claim 18 , wherein the first IoT device profile is attributed to the first IOT device after deployment of the first IoT device, and the first IoT device profile is a default IoT device profile that is dynamically modified using available data.

22. The system of claim 18 , wherein the first IoT device events are detected using passive monitoring.

23. The system of claim 18 , wherein the first IoT device events are detected using packet headers in messages sent to or from the first IoT device.

24. The system of claim 18 , wherein the first IoT device events are aggregated to form one or more composite first IoT device events using machine learning.

25. The system of claim 18 , wherein the first IoT device events are aggregated to form one or more composite first IoT device events using a device implemented as part of a local area network (LAN) that includes the first IoT device.

26. The system of claim 18 , wherein the first IoT device does not have a history of previously exhibited undesirable behavior, and the undesirable behavior includes anomalous behavior of the first IOT device.

27. The system of claim 18 , wherein the first IOT device has a history of previously exhibited undesirable behavior, and the undesirable behavior includes normal behavior of the first IoT device.

28. The system of claim 18 , wherein a plurality of discrete events are aggregated to form one or more composite events using machine learning.

29. The system of claim 28 , wherein the one or more composite events are formed using common factor aggregation.

30. The system of claim 29 , wherein a common factor used in the common factor aggregation includes a device profile common to a plurality of devices.

31. The system of claim 29 , wherein a common factor used in the common factor aggregation includes an operating system vendor common to a plurality of devices.

32. The system of claim 29 , wherein a common factor used in the common factor aggregation includes an operating system version common to a plurality of devices.

33. The system of claim 29 , wherein a common factor used in the common factor aggregation includes use of an application common to a plurality of devices.

34. The method of claim 29 , wherein a common factor used in the common factor aggregation includes communication via a particular subnetwork common to a plurality of devices.

Continuity (3)
Continuation 16445203 · Jun 18, 2019
Provisional Application 62686544 · Jun 18, 2018
Related Publication 20230370484A1 · Nov 16, 2023
References Cited (292)
US 6142682A · Skogby · 2000 [cited by applicant]
US 6877146B1 · Teig · 2005 [cited by applicant]
US 8146133B2 · Moon · 2012 [cited by applicant]
US 8159966B1 · Mabee · 2012 [cited by applicant]
US 8331229B1 · Hu · 2012 [cited by applicant]
US 8671099B2 · Kapoor · 2014 [cited by applicant]
US 8683598B1 · Cashin · 2014 [cited by applicant]
US 8850588B2 · Kumar · 2014 [cited by applicant]
US 8863276B2 · Giblin · 2014 [cited by applicant]
US 8874550B1 · Soubramanien · 2014 [cited by applicant]
US 8891528B2 · Moriarty · 2014 [cited by applicant]
US 8898788B1 · Aziz · 2014 [cited by applicant]
US 8973088B1 · Leung · 2015 [cited by applicant]
US 9112895B1 · Lin · 2015 [cited by examiner]
US 9324119B2 · Singh · 2016 [cited by applicant]
US 9378361B1 · Yen · 2016 [cited by applicant]
US 9516053B1 · Muddu · 2016 [cited by applicant]
US 9548987B1 · Poole · 2017 [cited by applicant]
US 9584536B2 · Nantel · 2017 [cited by applicant]
US 9600571B2 · Shaashua · 2017 [cited by applicant]
US 9609003B1 · Chmielewski · 2017 [cited by applicant]
US 9614742B1 · Zhang · 2017 [cited by applicant]
US 9661011B1 · Van Horenbeeck · 2017 [cited by applicant]
US 9692784B1 · Nenov · 2017 [cited by applicant]
US 9774604B2 · Zou · 2017 [cited by applicant]
US 9800603B1 · Sidagni · 2017 [cited by applicant]
US 9807110B2 · Harlacher · 2017 [cited by applicant]
US 9891907B2 · Searle · 2018 [cited by applicant]
US 9894085B1 · Dmitriyev · 2018 [cited by applicant]
US 9910874B1 · Jamail · 2018 [cited by applicant]
US 9961096B1 · Pierce · 2018 [cited by applicant]
US 9984344B2 · Singh · 2018 [cited by applicant]
US 10038700B1 · Duchin · 2018 [cited by applicant]
US 10043591B1 · Laborde · 2018 [cited by applicant]
US 10122747B2 · Mahaffey · 2018 [cited by applicant]
US 10129118B1 · Ghare · 2018 [cited by applicant]
US 10191794B2 · Smith · 2019 [cited by applicant]
US 10204312B2 · Singh · 2019 [cited by applicant]
US 10212176B2 · Wang · 2019 [cited by applicant]
US 10212178B2 · Cheng · 2019 [cited by applicant]
US 10229269B1 · Patton · 2019 [cited by applicant]
US 10237875B1 · Romanov · 2019 [cited by applicant]
US 10320613B1 · Cam-Winget · 2019 [cited by applicant]
US 10348739B2 · Greenspan · 2019 [cited by applicant]
US 10459827B1 · Aghdaie · 2019 [cited by applicant]
US 10489361B2 · Sisk · 2019 [cited by applicant]
US 10489714B2 · Lee · 2019 [cited by applicant]
US 10511620B2 · Schwartz · 2019 [cited by applicant]
US 10623389B2 · Childress · 2020 [cited by applicant]
US 10630728B2 · Ghosh · 2020 [cited by applicant]
US 10764315B1 · Carroll · 2020 [cited by applicant]
US 10862911B2 · Dezent · 2020 [cited by applicant]
US 10885393B1 · Sirianni · 2021 [cited by examiner]
US 10887306B2 · Gupta · 2021 [cited by applicant]
US 11005839B1 · Shahidzadeh · 2021 [cited by applicant]
US 11070568B2 · Ektare · 2021 [cited by applicant]
US 11115799B1 · Du · 2021 [cited by applicant]
US 11115823B1 · Heiland · 2021 [cited by applicant]
US 11310247B2 · Manadhata · 2022 [cited by applicant]
US 11455641B1 · Shahidzadeh · 2022 [cited by applicant]
US 11477202B2 · De Knijf · 2022 [cited by applicant]
US 20040243835A1 · Terzis · 2004 [cited by applicant]
US 20050044406A1 · Stute · 2005 [cited by applicant]
US 20050281291A1 · Stolfo · 2005 [cited by applicant]
US 20060095970A1 · Rajagopal · 2006 [cited by applicant]
US 20060265397A1 · Bryan · 2006 [cited by applicant]
US 20070094725A1 · Borders · 2007 [cited by applicant]
US 20080059536A1 · Brock · 2008 [cited by applicant]
US 20090180391A1 · Petersen · 2009 [cited by applicant]
US 20100054278A1 · Stolfo · 2010 [cited by applicant]
US 20100284282A1 · Golic · 2010 [cited by applicant]
US 20110022812A1 · Van Der Linden · 2011 [cited by applicant]
US 20110087626A1 · Yeleshwarapu · 2011 [cited by applicant]
US 20110239267A1 · Lyne · 2011 [cited by applicant]
US 20120065749A1 · Hunter · 2012 [cited by applicant]
US 20120102543A1 · Kohli · 2012 [cited by applicant]
US 20120174221A1 · Han · 2012 [cited by applicant]
US 20120240185A1 · Kapoor · 2012 [cited by applicant]
US 20130086261A1 · Lim · 2013 [cited by applicant]
US 20130173621A1 · Kapoor · 2013 [cited by applicant]
US 20130247190A1 · Spurlock · 2013 [cited by examiner]
US 20130305357A1 · Ayyagari · 2013 [cited by applicant]
US 20130305358A1 · Gathala · 2013 [cited by applicant]
US 20140006479A1 · Maloo · 2014 [cited by applicant]
US 20140157405A1 · Joll · 2014 [cited by applicant]
US 20140244834A1 · Guedalia · 2014 [cited by applicant]
US 20140281912A1 · Doi · 2014 [cited by applicant]
US 20140325670A1 · Singh · 2014 [cited by applicant]
US 20140337862A1 · Valencia · 2014 [cited by applicant]
US 20150039513A1 · Adjaoute · 2015 [cited by applicant]
US 20150055623A1 · Li · 2015 [cited by applicant]
US 20150161024A1 · Gupta · 2015 [cited by applicant]
US 20150199610A1 · Hershberg · 2015 [cited by applicant]
US 20150229654A1 · Perier · 2015 [cited by applicant]
US 20150256431A1 · Buchanan · 2015 [cited by applicant]
US 20150262067A1 · Sridhara · 2015 [cited by applicant]
US 20150271192A1 · Crowley · 2015 [cited by applicant]
US 20150293954A1 · Hsiao · 2015 [cited by applicant]
US 20150295945A1 · Canzanese, Jr. · 2015 [cited by applicant]
US 20150324559A1 · Boss · 2015 [cited by applicant]
US 20150356451A1 · Gupta · 2015 [cited by applicant]
US 20160006815A1 · Dong · 2016 [cited by applicant]
US 20160028750A1 · Di Pietro · 2016 [cited by applicant]
US 20160036819A1 · Zehavi · 2016 [cited by applicant]
US 20160048984A1 · Frigo · 2016 [cited by applicant]
US 20160119372A1 · Borlick · 2016 [cited by applicant]
US 20160128043A1 · Shuman · 2016 [cited by applicant]
US 20160164721A1 · Zhang · 2016 [cited by applicant]
US 20160173446A1 · Nantel · 2016 [cited by applicant]
US 20160173495A1 · Joo · 2016 [cited by applicant]
US 20160182497A1 · Smith · 2016 [cited by applicant]
US 20160196558A1 · Mercille · 2016 [cited by applicant]
US 20160210556A1 · Ben Simhon · 2016 [cited by applicant]
US 20160212099A1 · Zou · 2016 [cited by applicant]
US 20160218949A1 · Dasgupta · 2016 [cited by applicant]
US 20160261465A1 · Gupta · 2016 [cited by applicant]
US 20160267406A1 · Bodo · 2016 [cited by applicant]
US 20160267408A1 · Singh · 2016 [cited by examiner]
US 20160277435A1 · Salajegheh · 2016 [cited by applicant]
US 20160301707A1 · Cheng · 2016 [cited by applicant]
US 20160301717A1 · Dotan · 2016 [cited by applicant]
US 20160337127A1 · Schultz · 2016 [cited by applicant]
US 20160352685A1 · Park · 2016 [cited by applicant]
US 20160366141A1 · Smith · 2016 [cited by applicant]
US 20160366181A1 · Smith · 2016 [cited by applicant]
US 20160381030A1 · Chillappa · 2016 [cited by applicant]
US 20170006028A1 · Tunnell · 2017 [cited by applicant]
US 20170006135A1 · Siebel · 2017 [cited by applicant]
US 20170011406A1 · Tunnell · 2017 [cited by applicant]
US 20170013005A1 · Galula · 2017 [cited by applicant]
US 20170055913A1 · Bandyopadhyay · 2017 [cited by applicant]
US 20170063774A1 · Chen · 2017 [cited by applicant]
US 20170063889A1 · Muddu · 2017 [cited by applicant]
US 20170063905A1 · Muddu · 2017 [cited by applicant]
US 20170085580A1 · Thanos · 2017 [cited by applicant]
US 20170093915A1 · Ellis · 2017 [cited by applicant]
US 20170118237A1 · Devi Reddy · 2017 [cited by applicant]
US 20170118240A1 · Devi Reddy · 2017 [cited by applicant]
US 20170124660A1 · Srivastava · 2017 [cited by applicant]
US 20170126704A1 · Nandha Premnath · 2017 [cited by applicant]
US 20170149813A1 · Wright · 2017 [cited by applicant]
US 20170180380A1 · Bagasra · 2017 [cited by applicant]
US 20170180399A1 · Sukhomlinov · 2017 [cited by applicant]
US 20170188242A1 · Ghosh · 2017 [cited by applicant]
US 20170200061A1 · Julian · 2017 [cited by applicant]
US 20170214701A1 · Hasan · 2017 [cited by applicant]
US 20170230402A1 · Greenspan · 2017 [cited by applicant]
US 20170232300A1 · Tran · 2017 [cited by applicant]
US 20170235585A1 · Gupta · 2017 [cited by applicant]
US 20170235783A1 · Chen · 2017 [cited by applicant]
US 20170242414A1 · Coote · 2017 [cited by applicant]
US 20170244737A1 · Kuperman · 2017 [cited by applicant]
US 20170251007A1 · Fujisawa · 2017 [cited by applicant]
US 20170272554A1 · Kwan · 2017 [cited by applicant]
US 20170279685A1 · Mota · 2017 [cited by applicant]
US 20170289184A1 · C · 2017 [cited by applicant]
US 20170331671A1 · Olsson · 2017 [cited by applicant]
US 20170331906A1 · Choi · 2017 [cited by applicant]
US 20170339178A1 · Mahaffey · 2017 [cited by applicant]
US 20170344407A1 · Jeon · 2017 [cited by applicant]
US 20170346677A1 · Suryanarayana · 2017 [cited by applicant]
US 20180007055A1 · Infante-Lopez · 2018 [cited by applicant]
US 20180007058A1 · Zou · 2018 [cited by applicant]
US 20180012227A1 · Tunnell · 2018 [cited by applicant]
US 20180018684A1 · Orr · 2018 [cited by applicant]
US 20180027006A1 · Zimmermann · 2018 [cited by applicant]
US 20180027020A1 · Pallas · 2018 [cited by applicant]
US 20180039555A1 · Salunke · 2018 [cited by applicant]
US 20180078843A1 · Tran · 2018 [cited by applicant]
US 20180115574A1 · Ridley · 2018 [cited by applicant]
US 20180117446A1 · Tran · 2018 [cited by applicant]
US 20180117447A1 · Tran · 2018 [cited by applicant]
US 20180124096A1 · Schwartz · 2018 [cited by applicant]
US 20180139227A1 · Martin · 2018 [cited by applicant]
US 20180144139A1 · Cheng · 2018 [cited by applicant]
US 20180173881A1 · Oberheide · 2018 [cited by applicant]
US 20180191729A1 · Whittle · 2018 [cited by applicant]
US 20180191746A1 · De Knijf · 2018 [cited by applicant]
US 20180191755A1 · Monaco · 2018 [cited by applicant]
US 20180191848A1 · Bhattacharya · 2018 [cited by applicant]
US 20180205793A1 · Loeb · 2018 [cited by applicant]
US 20180212768A1 · Kawashima · 2018 [cited by applicant]
US 20180234302A1 · James · 2018 [cited by applicant]
US 20180234519A1 · Boyapalle · 2018 [cited by applicant]
US 20180248902A1 · Dãnilã-Dumitrescu et al. · 2018 [cited by applicant]
US 20180255084A1 · Kotinas · 2018 [cited by applicant]
US 20180261070A1 · Stevens · 2018 [cited by applicant]
US 20180264347A1 · Tran · 2018 [cited by applicant]
US 20180285234A1 · Degaonkar · 2018 [cited by applicant]
US 20180293387A1 · Bar-El · 2018 [cited by applicant]
US 20180295148A1 · Mayorgo · 2018 [cited by applicant]
US 20180302440A1 · Hu · 2018 [cited by applicant]
US 20180349598A1 · Harel · 2018 [cited by applicant]
US 20180349612A1 · Harel · 2018 [cited by applicant]
US 20180351972A1 · Yu · 2018 [cited by applicant]
US 20180357556A1 · Rai · 2018 [cited by applicant]
US 20180375887A1 · Dezent · 2018 [cited by applicant]
US 20190014169A1 · Chung · 2019 [cited by applicant]
US 20190019249A1 · Bhattacharjee · 2019 [cited by applicant]
US 20190081961A1 · Bansal · 2019 [cited by applicant]
US 20190089747A1 · Wang · 2019 [cited by applicant]
US 20190098028A1 · Ektare · 2019 [cited by applicant]
US 20190098058A1 · Ikegami · 2019 [cited by applicant]
US 20190109717A1 · Reddy · 2019 [cited by applicant]
US 20190121978A1 · Kraemer · 2019 [cited by applicant]
US 20190138512A1 · Pourmohammad · 2019 [cited by applicant]
US 20190182278A1 · Das · 2019 [cited by applicant]
US 20190253319A1 · Kampanakis · 2019 [cited by applicant]
US 20190268267A1 · Pignataro · 2019 [cited by applicant]
US 20190268305A1 · Xu · 2019 [cited by applicant]
US 20190296979A1 · Gupta · 2019 [cited by applicant]
US 20190349426A1 · Smith · 2019 [cited by applicant]
US 20190361917A1 · Tran · 2019 [cited by applicant]
US 20190373007A1 · Salunke · 2019 [cited by applicant]
US 20190373472A1 · Smith · 2019 [cited by applicant]
US 20190387399A1 · Weinberg · 2019 [cited by applicant]
US 20200036603A1 · Nieves · 2020 [cited by applicant]
US 20200074085A1 · Cheng · 2020 [cited by applicant]
US 20200076846A1 · Pandian · 2020 [cited by applicant]
US 20200076853A1 · Pandian · 2020 [cited by applicant]
US 20200117690A1 · Tran · 2020 [cited by applicant]
US 20200156654A1 · Boss · 2020 [cited by applicant]
US 20200162278A1 · Delaney · 2020 [cited by applicant]
US 20200162503A1 · Shurtleff · 2020 [cited by applicant]
US 20200177485A1 · Shurtleff · 2020 [cited by applicant]
US 20200177589A1 · Mangalvedkar · 2020 [cited by applicant]
US 20200195679A1 · Du · 2020 [cited by applicant]
US 20200211721A1 · Ochoa · 2020 [cited by applicant]
US 20200213146A1 · Kodam · 2020 [cited by applicant]
US 20200285457A1 · Meriac · 2020 [cited by applicant]
US 20200285997A1 · Bhattacharyya · 2020 [cited by applicant]
US 20200366717A1 · Chaubey · 2020 [cited by applicant]
US 20200409957A1 · Zhang · 2020 [cited by applicant]
US 20210058430A1 · Novak · 2021 [cited by applicant]
US 20210203615A1 · Roy · 2021 [cited by applicant]
US 20210360406A1 · Heiland · 2021 [cited by applicant]
US 20220060491A1 · Achleitner · 2022 [cited by applicant]
US 20220086071A1 · Sivaraman · 2022 [cited by applicant]
US 20220138634A1 · Covell · 2022 [cited by applicant]
US 20220159020A1 · Wang · 2022 [cited by applicant]
US 20220210065A1 · Khanna · 2022 [cited by applicant]
US 20220210066A1 · Khanna · 2022 [cited by applicant]
US 20230049886A1 · Sesha · 2023 [cited by applicant]
CA 2904463 · 2020 [cited by applicant]
CN 101719899 · 2010 [cited by applicant]
CN 102025577 · 2012 [cited by applicant]
CN 102291430 · 2013 [cited by applicant]
CN 107862468 · 2018 [cited by applicant]
CN 104837158 · 2018 [cited by applicant]
CN 108650133 · 2018 [cited by applicant]
CN 105659633 · 2020 [cited by applicant]
CN 107135093 · 2020 [cited by applicant]
CN 108306911 · 2020 [cited by applicant]
EP 3136297 · 2017 [cited by applicant]
EP 3576373 · 2019 [cited by applicant]
JP 2016532957 · 2016 [cited by applicant]
JP 2018513467 · 2018 [cited by applicant]
JP 2019536144 · 2019 [cited by applicant]
JP 2020503784 · 2020 [cited by applicant]
KR 20170059546 · 2017 [cited by applicant]
WO 2019218874 · 2019 [cited by applicant]
Al-Shaer et al., Design and Implementation of Firewall Policy Advisor Tools, 2002. [cited by applicant]
Al-Shaer et al., Firewall Policy Advisor for Anomaly Discovery and Rule Editing, Integrated Network Management VIII, 2003. [cited by applicant]
Arash Fasihi , Rule Based Inference and Action Selection Based on Monitoring Data in IoT, Dec. 1, 2015. [cited by applicant]
Author Unknown, Cisco Encrypted Traffic Analytics, Feb. 10, 2021. [cited by applicant]
Blackstock et al., IoT Interoperability: A Hub-based Approach, 2014, IEEE International Conference on the Internet of Things (IOT), pp. 80-84. [cited by applicant]
Charu C. Aggarwal, Outlier Analysis, Feb. 10, 2013, Retrieved from the Internet, URL:https://web.archive.org/web/20130210212057/http://charuaggarwal.net/outlierbook.pdf. [cited by applicant]
Charyyev et al., Locality-Sensitive IoT Network Traffic Fingerprinting for Device Identification, IEEE Internet of Things Journal, 2020, vol. 8, No. 3, pp. 1272-1281. [cited by applicant]
Chen et al., A Model-Based Validated Autonomic Approach to Self-Protect Computing Systems, IEEE Internet of Things Journal, Oct. 2014, pp. 446-460, vol. 1, No. 5. [cited by applicant]
Cramer et al., Detecting Anomalies in Device Event Data in the IoT, Proceedings of the 3td International Conference on Internet of Things, Big Data and Security, Mar. 21, 2018, pp. 52-62. [cited by applicant]
Du et al., A Lightweight Flow Feature-Based IoT Device Identification Scheme, Security and Communication Networks, 2022. [cited by applicant]
Fredj et al., A Scalable IoT Service Search Based on Clustering and Aggregation, 2013 IEEE International Conference on Green Computing and Communication and IEEE Internet of Things and IEEE Cyber, Physical and Social Co… [cited by applicant]
Hirofumi Nakakoji, et al., “Study of the Incident Tendency Detection Method on Frequency Analysis,” Technical Report of IEICE, Japan, The Institute of Electronics, Information and Communication Engineers (IEICE), Jul. 1… [cited by applicant]
International Application No. PCT/US2016/025661, International Search Report and Written Opinion mailed Jul. 7, 2016. [cited by applicant]
Li et al., A Distributed Consensus Algorithm for Decision Making in Service-Oriented Internet of Things, Old Dominion University, ODU Digital Commons, 2014. [cited by applicant]
Liu et al., A Lightweight Anomaly Mining Algorithm in the Internet of Things, 2014 IEEE 5th International Conference on Software Engineering and Service Science, 2014, pp. 1142-1145. [cited by applicant]
Martin et al., Requirements and Recommendations for CWE Compatibility and CWE Effectiveness, Version 1.0, Jul. 28, 2011. [cited by applicant]
Midi et al., Kalis—A System for Knowledge-driven Adaptable Intrusion Detection for the Internet of Things, 2017 IEEE 37th International Conference on Distributed Computing Systems, pp. 656-666. [cited by applicant]
Miloslavskaya et al., Ensuring Information Security for Internet of Things, 2017, IEEE 5th International Conference of Future Internet of Things and Cloud, pp. 62-69. [cited by applicant]
National Electrical Manufacturers Association, Manufacturer Disclosure Statement for Medical Device Security, HIMSS/NEMA Standard HN Jan. 2013, 2013. [cited by applicant]
Nguyen et al., A Software-Defined Model for IoT Clusters: Enabling Applications on Demand, Faculty of Engineering and IT, University of Technology Sydney, Australia, IEEE Xplore, Apr. 23, 2018. [cited by applicant]
Sivanathan et al., Classifying IoT Devices in Smart Environments Using Network Traffic Characteristics, IEEE, TMC, No. 8, pp. 1745-1759, Aug. 2018. [cited by applicant]
Sivanathan et al., Detecting Behavioral Change of IoT Devices Using Clustering-Based Network Traffic Modeling, IEEE LCN 2019, Mar. 30, 2020. [cited by applicant]
Sivanathan et al., Inferring IoT Device Types from Network Behavior Using Unsupervised Clustering, IEEE ICN 2019, Oct. 2019. [cited by applicant]
Zhao et al., A Few-Shot Learning Based Approach to IoT Traffic Classification, IEEE Communications Letters, 2021. [cited by applicant]
Meidan et al., ProfilIoT: A Machine Learning Approach for IoT Device Identification Based on Network Traffic Analysis, In Proceedings of the Symposium on Applied Computing (SAC'17), Apr. 3-7, 2017, pp. 506-509. [cited by applicant]
Fahim et al., Anomaly detection, analysis and prediction techniques in IoT environment: A systematic literature review, IEEE Access, vol. 7, 2019, pp. 81664-81681. [cited by applicant]
Nassif et al., Machine learning for anomaly detection: A systematic review, IEEE Access, vol. 9, 2021, pp. 78658-78700. [cited by applicant]
Liu et al., Deep anomaly detection for time-series data in industrial IoT: A communication-efficient on-device federated learning approach, IEEE Internet of Things Journal, vol. 8, No. 8, Apr. 15, 2021, pp. 6348-6358. [cited by applicant]
Liu et al., Noise removal in the presence of significant anomalies for industrial IoT sensor data in manufacturing, IEEE Internet of Things Journal, vol. 7, No. 8, Aug. 2020, pp. 7084-7096. [cited by applicant]
Pahl et al., All eyes on you: Distributed Multi-Dimensional IoT microservice anomaly detection, 14th International Conference on Network and Service Management (CNSM), IEEE, 2018, pp. 72-80. [cited by applicant]
Miettinen et al., IoT Sentinel Demo: Automated Device-Type Id entification for Security Enforcement in IoT, IEEE 37th International Conference on Distributed Computing Systems (ICDCS), Jun. 5-8, 2017, pp. 2177-2184, htt… [cited by applicant]