IP Library Granted Patent US 12,519,818
Granted Patent B2
US 12,519,818 · App. 18/506,900 · Granted Jan 6, 2026

Disaster scenario based inferential analysis using feedback for extracting and combining cyber risk information

Inventors: George Y. Ng (San Mateo, CA); Frank Beier (San Carlos, CA); Olivier Giulieri (San Mateo, CA); Yoshifumi Yamamoto (Palo Alto, CA); Zheng Cheung (Fremont, CA)
Assignee: Guidewire Software, Inc.
H04L63/1433G06Q40/06H04L63/20H04L69/40
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Quick Facts
Patent No.
US 12,519,818
App. No.
18/506,900
Filed
Nov 10, 2023
Granted
Jan 6, 2026
Kind
B2
Art Unit
2498
USPC
726/25
Abstract

Assessing risk of a cyber security failure in a computer network of an entity includes: assessing risk of an entity, using a computer agent configured to collect information from at least publicly accessible Internet elements, and automatically recommending, based at least in part on the assessed risk, changes to reduce the assessed risk to mitigate the theoretical damage. The assessed risk comprises a cyber security failure risk in a computer network of the entity; and the assessing of risk comprises: generating a disaster scenario that comprises elements of a disaster event; modeling the disaster scenario against a profile of the entity; and determining theoretical damage based at least in part on the modeling.

Claims (59)

1 . A method, comprising:

assessing a risk of cyber security failure of an entity, using a computer agent configured to collect information from at least publicly accessible Internet elements, wherein the assessing of the risk of cyber security failure comprises:

generating a disaster scenario that comprises elements of a disaster event; and

determining a cyber security impact of the disaster scenario on the entity based at least in part on modeling damage caused by the disaster scenario; and

based at least in part on the assessing, providing output usable to reduce the assessed risk of cyber security failure, comprising:

providing the output based on a first disaster scenario or a second disaster scenario, wherein the first disaster scenario is different from the second disaster scenario, wherein the first disaster scenario is modeled based on a first disaster model, wherein the second disaster scenario is modeled based on a second disaster model, wherein the first disaster model is different from the second disaster model, wherein the first disaster model is implemented using a first machine learning technique, wherein the second disaster model is implemented using a second machine learning technique, and wherein providing the output comprises providing one or more changes including one or more of: an update to a cyber security policy, a setting to the cyber security policy, a network change, and/or a network setting.

2 . The method of claim 1 , further comprising:

generating recommended suggestions for a computer network relative to the disaster scenario and based at least in part on the collected information obtained for the computer network and the entity, wherein the recommended suggestions comprise one or more changes to reduce the assessed risk of cyber security failure; and

automatically recommending at least one change to reduce the assessed risk of cyber security failure.

3 . The method of claim 2 , further comprising:

determining that the entity has enacted at least a portion of the at least one automatically recommended change, and in response, automatically reassessing the risk of the entity; and

dynamically re-determining, based at least in part on the reassessed risk, an update, a setting, or both to a cyber security policy.

4 . The method of claim 3 , wherein the cyber security policy includes:

a cyber security policy from another entity;

a product warranty for first and/or third-party costs that the entity purchases from at least one of a networking, security product, and services provider; or

both.

5 . The method of claim 1 , further comprising re-determining the risk of cyber security failure of the entity at least in part by incorporating outcome data of the modeling.

6 . The method of claim 1 , further comprising generating optimized or improved disaster scenarios based at least in part on outcomes of disaster scenario modeling of a plurality of computer networks.

7 . The method of claim 1 , wherein the computer agent is further configured to perform: collecting information from a computer network of the entity, analyzing information from the computer network of the entity, or both.

8 . A system, comprising:

one or more hardware processors configured to:

assess a risk of cyber security failure of an entity, using a computer agent configured to collect information from at least publicly accessible Internet elements, wherein the assessing of the risk of cyber security failure comprises:

generating a disaster scenario that comprises elements of a disaster event; and

determining a cyber security impact of the disaster scenario on the entity based at least in part on modeling damage caused by the disaster scenario; and

based at least in part on the assessing, provide output usable to reduce the assessed risk of cyber security failure, comprising:

providing the output based on a first disaster scenario or a second disaster scenario, wherein the first disaster scenario is different from the second disaster scenario, wherein the first disaster scenario is modeled based on a first disaster model, wherein the second disaster scenario is modeled based on a second disaster model, wherein the first disaster model is different from the second disaster model, wherein the first disaster model is implemented using a first machine learning technique, wherein the second disaster model is implemented using a second machine learning technique, and wherein providing the output comprises providing one or more changes including one or more of: an update to a cyber security policy, a setting to the cyber security policy, a network change, and/or a network setting.

9 . The system recited in claim 8 , wherein the one or more hardware processors are further configured to:

generate recommended suggestions for a computer network relative to the disaster scenario and based at least in part on the collected information obtained for the computer network and the entity, wherein the recommended suggestions comprise one or more changes to reduce the assessed risk of cyber security failure; and

automatically recommend at least one change to reduce the assessed risk of cyber security failure.

10 . The system recited in claim 9 , wherein the one or more hardware processors are further configured to:

determine that the entity has enacted at least a portion of the at least one automatically recommended change, and in response, automatically reassess the risk of the entity; and

dynamically re-determine, based at least in part on the reassessed risk, an update, a setting, or both to a cyber security policy.

11 . The system recited in claim 10 , wherein the cyber security policy includes:

a cyber security policy from another entity;

a product warranty for first and/or third-party costs that the entity purchases from at least one of a networking, security product, and services provider; or

both.

12 . The system recited in claim 10 , wherein the one or more hardware processors are further configured to re-determine the risk of cyber security failure of the entity at least in part by incorporating outcome data of the modeling.

13 . The system recited in claim 8 , wherein the one or more hardware processors are further configured to generate optimized or improved disaster scenarios based at least in part on outcomes of disaster scenario modeling of a plurality of computer networks.

14 . The system recited in claim 8 , wherein the computer agent is further configured to perform: collecting information from a computer network of the entity, analyzing information from the computer network of the entity, or both.

15 . A computer program product embodied in a non-transitory computer readable storage medium and comprising computer instructions for:

assessing a risk of cyber security failure of an entity, using a computer agent configured to collect information from at least publicly accessible Internet elements, wherein the assessing of the risk of cyber security failure comprises:

generating a disaster scenario that comprises elements of a disaster event; and

determining a cyber security impact of the disaster scenario on the entity based at least in part on modeling damage caused by the disaster scenario; and

based at least in part on the assessing, provide output usable to reduce the assessed risk of cyber security failure, comprising:

providing the output based on a first disaster scenario or a second disaster scenario, wherein the first disaster scenario is different from the second disaster scenario, wherein the first disaster scenario is modeled based on a first disaster model, wherein the second disaster scenario is modeled based on a second disaster model, wherein the first disaster model is different from the second disaster model, wherein the first disaster model is implemented using a first machine learning technique, wherein the second disaster model is implemented using a second machine learning technique, and wherein providing the output comprises providing one or more changes including one or more of: an update to a cyber security policy, a setting to the cyber security policy, a network change, and/or a network setting.

16 . The computer program product of claim 15 , further comprising computer instructions for:

generating recommended suggestions for a computer network relative to the disaster scenario and based at least in part on the collected information obtained for the computer network and the entity, wherein the recommended suggestions comprise one or more changes to reduce the assessed risk of cyber security failure; and

automatically recommending at least one change to reduce the assessed risk of cyber security failure.

17 . The computer program product of claim 16 , further comprising computer instructions for:

determining that the entity has enacted at least a portion of the at least one automatically recommended change, and in response, automatically reassessing the risk of the entity; and

dynamically re-determining, based at least in part on the reassessed risk, an update, a setting, or both to a cyber security policy.

18 . The computer program product of claim 17 , wherein the cyber security policy includes:

a cyber security policy from another entity;

a product warranty for first and/or third-party costs that the entity purchases from at least one of a networking, security product, and services provider; or

both.

19 . The computer program product of claim 15 , further comprising computer instructions for:

re-determining the risk of cyber security failure of the entity at least in part by incorporating outcome data of the modeling.

20 . The computer program product of claim 15 , further comprising computer instructions for:

generating optimized or improved disaster scenarios based at least in part on outcomes of disaster scenario modeling of a plurality of computer networks.

Assignments (1)
PATENT SECURITY AGREEMENT Recorded Dec 3, 2024
From: GUIDEWIRE SOFTWARE, INC.
To: BANK OF AMERICA, N.A., AS ADMINISTRATIVE AGENT
Reel/Frame 069476/0488 →
Continuity (11)
Continuation 17465739 · Sep 2, 2021
Continuation 16582977 · Sep 25, 2019
Continuation 15972027 · May 4, 2018
Continuation 15374212 · Dec 9, 2016
Continuation In Part 15141779 · Apr 28, 2016
Continuation In Part 14931510 · Nov 3, 2015
Continuation In Part 14585051 · Dec 29, 2014
Continuation In Part PCTUS2015067968 · Dec 29, 2015
Continuation 14614897 · Feb 5, 2015
Provisional Application 62098238 · Dec 30, 2014
Related Publication 20240187442A1 · Jun 6, 2024
References Cited (222)
US 5243428A · Challapali · 1993 [cited by applicant]
US 5535383A · Gower · 1996 [cited by applicant]
US 5754973A · Akune · 1998 [cited by applicant]
US 5920861A · Hall · 1999 [cited by applicant]
US 5949876A · Ginter · 1999 [cited by applicant]
US 5987440A · O'Neil · 1999 [cited by applicant]
US 6269349B1 · Aieta · 2001 [cited by applicant]
US 6374358B1 · Townsend · 2002 [cited by applicant]
US 6839689B2 · Aieta · 2005 [cited by applicant]
US 6980927B2 · Tracy · 2005 [cited by applicant]
US 7047419B2 · Black · 2006 [cited by applicant]
US 7324952B2 · Hisano · 2008 [cited by applicant]
US 7680659B2 · Gao · 2010 [cited by applicant]
US 7711646B2 · Cianciarulo · 2010 [cited by applicant]
US 8332242B1 · Medina, III · 2012 [cited by applicant]
US 8448245B2 · Banerjee · 2013 [cited by applicant]
US 8468599B2 · Mccusker · 2013 [cited by applicant]
US 8484066B2 · Miller · 2013 [cited by applicant]
US 8494955B2 · Quarterman · 2013 [cited by applicant]
US 8577775B1 · Gerber · 2013 [cited by applicant]
US 8601587B1 · Powell · 2013 [cited by applicant]
US 8699767B1 · Khosla · 2014 [cited by applicant]
US 8744894B2 · Christiansen · 2014 [cited by applicant]
US 8973088B1 · Leung · 2015 [cited by applicant]
US 9027125B2 · Kumar · 2015 [cited by applicant]
US 9031951B1 · Baluja · 2015 [cited by applicant]
US 9043905B1 · Allen · 2015 [cited by examiner]
US 9100430B1 · Seiver · 2015 [cited by applicant]
US 9241008B2 · Powell · 2016 [cited by applicant]
US 9253203B1 · Ng · 2016 [cited by applicant]
US 9292881B2 · Alperovitch · 2016 [cited by applicant]
US 9367694B2 · Eck · 2016 [cited by applicant]
US 9373144B1 · Ng · 2016 [cited by applicant]
US 9471777B1 · Juels · 2016 [cited by applicant]
US 9521160B2 · Ng · 2016 [cited by applicant]
US 9613442B2 · Pan · 2017 [cited by applicant]
US 9646428B1 · Konrardy · 2017 [cited by applicant]
US 9699209B2 · Ng · 2017 [cited by applicant]
US 9715711B1 · Konrardy · 2017 [cited by applicant]
US 9893970B2 · Gauvin · 2018 [cited by applicant]
US 9894036B2 · Weinberger · 2018 [cited by applicant]
US 10050989B2 · Ng · 2018 [cited by applicant]
US 10050990B2 · Ng · 2018 [cited by applicant]
US 10099297B2 · Lemmer · 2018 [cited by applicant]
US 10102589B1 · Tofte · 2018 [cited by applicant]
US 10230764B2 · Ng · 2019 [cited by applicant]
US 10326786B2 · Gladstone · 2019 [cited by applicant]
US 10404737B1 · Sweeney · 2019 [cited by applicant]
US 10404748B2 · Parthasarathi · 2019 [cited by applicant]
US 10498757B2 · Pickles · 2019 [cited by applicant]
US 10574539B2 · Brown · 2020 [cited by applicant]
US 10656993B2 · Thatcher · 2020 [cited by applicant]
US 20020026335A1 · Honda · 2002 [cited by applicant]
US 20020091551A1 · Parisi · 2002 [cited by applicant]
US 20030014342A1 · Vande Pol · 2003 [cited by applicant]
US 20030014344A1 · Chacko · 2003 [cited by applicant]
US 20030028803A1 · Bunker · 2003 [cited by applicant]
US 20030040942A1 · Hooten · 2003 [cited by applicant]
US 20030084349A1 · Friedrichs · 2003 [cited by applicant]
US 20030126049A1 · Nagan · 2003 [cited by applicant]
US 20030135758A1 · Turner · 2003 [cited by applicant]
US 20030154393A1 · Young · 2003 [cited by applicant]
US 20030236990A1 · Hrastar · 2003 [cited by applicant]
US 20040006532A1 · Lawrence · 2004 [cited by applicant]
US 20040010709A1 · Baudoin · 2004 [cited by applicant]
US 20040024693A1 · Lawrence · 2004 [cited by applicant]
US 20040049698A1 · Ott · 2004 [cited by applicant]
US 20040064726A1 · Girouard · 2004 [cited by applicant]
US 20040167793A1 · Masuoka · 2004 [cited by applicant]
US 20040260945A1 · Raikar · 2004 [cited by applicant]
US 20050015624A1 · Ginter · 2005 [cited by applicant]
US 20050044418A1 · Miliefsky · 2005 [cited by applicant]
US 20050096944A1 · Ryan · 2005 [cited by applicant]
US 20050097320A1 · Golan · 2005 [cited by applicant]
US 20050131828A1 · Gearhart · 2005 [cited by applicant]
US 20050132225A1 · Gearhart · 2005 [cited by applicant]
US 20050261943A1 · Quarterman · 2005 [cited by applicant]
US 20050278786A1 · Tippett · 2005 [cited by applicant]
US 20060020814A1 · Lieblich · 2006 [cited by applicant]
US 20060062443A1 · Basu · 2006 [cited by applicant]
US 20060184473A1 · Eder · 2006 [cited by applicant]
US 20060265746A1 · Farley · 2006 [cited by applicant]
US 20070005680A1 · Jrad · 2007 [cited by examiner]
US 20070180490A1 · Renzi · 2007 [cited by applicant]
US 20070192867A1 · Miliefsky · 2007 [cited by applicant]
US 20070294118A1 · Tait · 2007 [cited by applicant]
US 20070298720A1 · Wolman · 2007 [cited by applicant]
US 20080016563A1 · Mcconnell · 2008 [cited by applicant]
US 20080047016A1 · Spoonamore · 2008 [cited by applicant]
US 20080162377A1 · Pinkas · 2008 [cited by applicant]
US 20080167920A1 · Schmidt · 2008 [cited by applicant]
US 20080250064A1 · Duchon · 2008 [cited by applicant]
US 20080280637A1 · Shaffer · 2008 [cited by applicant]
US 20090024663A1 · Mcgovern · 2009 [cited by applicant]
US 20090037323A1 · Feinstein · 2009 [cited by applicant]
US 20090063365A1 · Pinkas · 2009 [cited by applicant]
US 20090126018A1 · Keohane · 2009 [cited by applicant]
US 20090271863A1 · Govindavajhala · 2009 [cited by examiner]
US 20090319342A1 · Shilman · 2009 [cited by applicant]
US 20100046553A1 · Daigle · 2010 [cited by applicant]
US 20100114634A1 · Christiansen · 2010 [cited by applicant]
US 20100153156A1 · Guinta · 2010 [cited by examiner]
US 20100205014A1 · Sholer · 2010 [cited by applicant]
US 20100229187A1 · Marwah · 2010 [cited by applicant]
US 20110036909A1 · Berkun · 2011 [cited by applicant]
US 20110078073A1 · Annappindi · 2011 [cited by applicant]
US 20110154497A1 · Bailey, Jr. · 2011 [cited by applicant]
US 20110161116A1 · Peak · 2011 [cited by applicant]
US 20110239267A1 · Lyne · 2011 [cited by applicant]
US 20110244798A1 · Daigle · 2011 [cited by applicant]
US 20110277034A1 · Hanson · 2011 [cited by applicant]
US 20110289597A1 · Hinds · 2011 [cited by applicant]
US 20110295722A1 · Reisman · 2011 [cited by applicant]
US 20110313930A1 · Bailey, Jr. · 2011 [cited by applicant]
US 20120011077A1 · Bhagat · 2012 [cited by applicant]
US 20120041790A1 · Koziol · 2012 [cited by applicant]
US 20120046989A1 · Baikalov · 2012 [cited by applicant]
US 20120059779A1 · Syed · 2012 [cited by applicant]
US 20120079598A1 · Brock · 2012 [cited by applicant]
US 20120089617A1 · Frey · 2012 [cited by applicant]
US 20120096558A1 · Evrard · 2012 [cited by applicant]
US 20120159624A1 · König · 2012 [cited by applicant]
US 20120215575A1 · Deb · 2012 [cited by applicant]
US 20120239438A1 · Hemmings · 2012 [cited by applicant]
US 20120284158A1 · Kovac · 2012 [cited by applicant]
US 20120300975A1 · Chalamala · 2012 [cited by applicant]
US 20130055404A1 · Khalili · 2013 [cited by applicant]
US 20130073473A1 · Heath · 2013 [cited by applicant]
US 20130104236A1 · Ray · 2013 [cited by examiner]
US 20130188475A1 · Lim · 2013 [cited by applicant]
US 20130191829A1 · Shimokawa · 2013 [cited by applicant]
US 20130218670A1 · Spears · 2013 [cited by applicant]
US 20130239167A1 · Sreenivas · 2013 [cited by applicant]
US 20130239168A1 · Sreenivas · 2013 [cited by applicant]
US 20130239177A1 · Sigurdson · 2013 [cited by applicant]
US 20130283336A1 · Macy · 2013 [cited by examiner]
US 20130346328A1 · Agle · 2013 [cited by applicant]
US 20130347060A1 · Hazzani · 2013 [cited by applicant]
US 20140007190A1 · Alperovitch · 2014 [cited by applicant]
US 20140019171A1 · Koziol · 2014 [cited by applicant]
US 20140067713A1 · Gerber · 2014 [cited by applicant]
US 20140067716A1 · Gerber · 2014 [cited by applicant]
US 20140122163A1 · Simpson · 2014 [cited by examiner]
US 20140137257A1 · Martinez · 2014 [cited by applicant]
US 20140142988A1 · Grosso · 2014 [cited by applicant]
US 20140181982A1 · Guo · 2014 [cited by applicant]
US 20140200930A1 · Zizzamia · 2014 [cited by applicant]
US 20140215621A1 · Xaypanya · 2014 [cited by applicant]
US 20140257917A1 · Spencer · 2014 [cited by examiner]
US 20140257918A1 · Spencer · 2014 [cited by examiner]
US 20140328179A1 · Kabakura · 2014 [cited by applicant]
US 20140379708A1 · Fox · 2014 [cited by applicant]
US 20150088595A1 · Chillar · 2015 [cited by applicant]
US 20150095206A1 · Van Heerden · 2015 [cited by applicant]
US 20150100442A1 · Van Heerden · 2015 [cited by applicant]
US 20150100443A1 · Van Heerden · 2015 [cited by applicant]
US 20150106260A1 · Andrews · 2015 [cited by applicant]
US 20150188949A1 · Mahaffey et al. · 2015 [cited by applicant]
US 20150269383A1 · Lang · 2015 [cited by examiner]
US 20150271142A1 · Oliphant · 2015 [cited by applicant]
US 20150324559A1 · Boss · 2015 [cited by applicant]
US 20150331932A1 · Georges · 2015 [cited by applicant]
US 20150341389A1 · Kurakami · 2015 [cited by applicant]
US 20150373043A1 · Wang · 2015 [cited by applicant]
US 20150379488A1 · Ruff · 2015 [cited by applicant]
US 20150381662A1 · Nair · 2015 [cited by examiner]
US 20160099963A1 · Mahaffey · 2016 [cited by applicant]
US 20160148332A1 · Stibel · 2016 [cited by applicant]
US 20160155066A1 · Drame · 2016 [cited by applicant]
US 20160162924A1 · Rathod · 2016 [cited by applicant]
US 20160189301A1 · Ng · 2016 [cited by applicant]
US 20160197953A1 · King-Wilson · 2016 [cited by applicant]
US 20160205138A1 · Krishnaprasad · 2016 [cited by applicant]
US 20160212169A1 · Knjazihhin · 2016 [cited by applicant]
US 20160234247A1 · Ng · 2016 [cited by applicant]
US 20160248799A1 · Ng · 2016 [cited by applicant]
US 20160248800A1 · Ng · 2016 [cited by applicant]
US 20160294854A1 · Parthasarathi · 2016 [cited by applicant]
US 20160306979A1 · Kotler · 2016 [cited by applicant]
US 20170085595A1 · Ng · 2017 [cited by applicant]
US 20170093904A1 · Ng · 2017 [cited by applicant]
US 20170093905A1 · Ng · 2017 [cited by applicant]
US 20170116552A1 · Deodhar · 2017 [cited by applicant]
US 20170142140A1 · Muddu · 2017 [cited by applicant]
US 20170187745A1 · Ng · 2017 [cited by applicant]
US 20180025157A1 · Titonis · 2018 [cited by applicant]
US 20180359276A1 · Ng · 2018 [cited by applicant]
US 20190035027A1 · Ng · 2019 [cited by applicant]
US 20210358046A1 · Roll · 2021 [cited by applicant]
US 20220245727A1 · Roll · 2022 [cited by applicant]
EP 3675455 · 2020 [cited by applicant]
JP 2006295910 · 2006 [cited by applicant]
TW 201636937 · 2016 [cited by applicant]
WO 2014036396 · 2014 [cited by applicant]
WO 2016109162 · 2016 [cited by applicant]
WO 2016109608 · 2016 [cited by applicant]
WO 2017078986 · 2017 [cited by applicant]
Bohme et al., “Models and Measures for Correlation in Cyber-Insurance,” Workshop on the Economics of Information Security (WEIS), Jun. 2006, Retrieved from <http://www.econinfosec.org/archive/weis2006/docs/16.pdf>. [cited by applicant]
Intemational Search Report & Written Opinion dated Feb. 10, 2016 in Patent Cooperation Treaty Application No. PCT/US2015/065365, filed Dec. 11, 2015. [cited by applicant]
Intemational Search Report & Written Opinion dated Feb. 26, 2016 in Patent Cooperation Treaty Application No. PCT/US2015/067968, filed Dec. 29, 2015. [cited by applicant]
International Search Report and Written Opinion of the International Searching Authority, Patent Cooperation Treaty Application No. PCT/US2016/058711, Dec. 8, 2016, 9 pages. [cited by applicant]
Martin Salois, “Password Complexity Recommendations”, Defense Research and Development Canada, Oct. 2014, pp. 1-34. [cited by applicant]
Mathew et al., “Intruders and Password Management,” International Journal of Science Technology & Engineering, Oct. 2015, pp. 312-315. [cited by applicant]
Notice of Allowance mailed Aug. 24, 2017 for U.S. Appl. No. 15/099,297, filed Apr. 14, 2016. [cited by applicant]
Notice of Allowance mailed Jan. 3, 2017 for U.S. Appl. No. 15/142,997, filed Apr. 29, 2016. [cited by applicant]
Notice of Allowance mailed Jul. 29, 2016 in U.S. Appl. No. 15/141,779, filed Apr. 28, 2016. [cited by applicant]
Notice of Allowance mailed Mar. 15, 2016 for U.S. Appl. No. 14/931,510, filed Nov. 3, 2015. [cited by applicant]
Notice of Allowance mailed Sep. 25, 2015 for U.S. Appl. No. 14/585,051, filed Dec. 29, 2014. [cited by applicant]
Office Action mailed Apr. 1, 2015 for U.S. Appl. No. 14/585,051, filed Dec. 29, 2014. [cited by applicant]
Office Action mailed Apr. 20, 2015 in U.S. Appl. No. 14/614,897, filed Feb. 5, 2015. [cited by applicant]
Office Action mailed Aug. 23, 2017 in U.S. Appl. No. 15/371,047, filed Dec. 6, 2016. [cited by applicant]
Office Action mailed Jul. 29, 2016 in U.S. Appl. No. 15/142,997, filed Apr. 29, 2016. [cited by applicant]
Office Action mailed Mar. 14, 2017 in U.S. Appl. No. 15/099,297, filed Apr. 14, 2016. [cited by applicant]
Office Action mailed May 23, 2017 in U.S. Appl. No. 15/457,921, filed Mar. 13, 2017. [cited by applicant]
Office Action mailed Oct. 16, 2015 in U.S. Appl. No. 14/614,897, filed Feb. 5, 2015. [cited by applicant]
Office Action mailed Sep. 7, 2016 for U.S. Appl. No. 15/099,297, filed Apr. 14, 2016. [cited by applicant]
Office Action mailed Sep. 7, 2017 in U.S. Appl. No. 15/373,298, filed Dec. 8, 2016. [cited by applicant]
Office Action mailed Sep. 7, 2017 in U.S. Appl. No. 15/374,212, filed Dec. 9, 2016. [cited by applicant]
Raftery et al., “Variable Selection for Model-Based Clustering,” Journal of the American Statistical Association, Mar. 2006, pp. 168-178, http://www.stat.washington.edu/rattery/Research/PDF/dean2006.pdf. [cited by applicant]
Santos et al., Method of Automated Cyber Risk Assessment, Insurance Underwriting, and Remediation, Cisco Systems, Inc. 2017. [cited by applicant]
Scarfone et al. NIST Special Publication 800-118. “Guide to Enterprise Password Management (Draft)”, Apr. 2009, NIST (National Institute of Standards and Technology), pp. 1-40. [cited by applicant]
U.S. Appl. No. 14/614,897, filed Feb. 5, 2015. [cited by applicant]