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Michael Joseph O'Dea, 48Estero, FL

Michael O'Dea Phones & Addresses

Estero, FL   

Aliso Viejo, CA   

Mission Viejo, CA   

Los Angeles, CA   

Lee, FL   

Marina del Rey, CA   

Cortlandt Manor, NY   

Mentions for Michael Joseph O'Dea

Career records & work history

Lawyers & Attorneys

Michael O'Dea Photo 1

Michael O'Dea - Lawyer

ISLN:
922074509
Admitted:
2008
Michael O'Dea Photo 2

Michael O'Dea - Lawyer

ISLN:
1001172340
Admitted:
2021

Resumes & CV records

Resumes

Michael O'Dea Photo 27

Michael O'dea

Education:
Mass Bay Community College

Publications & IP owners

Us Patents

System And Method Of Managing Network Security Risks

US Patent:
8201257, Jun 12, 2012
Filed:
Mar 31, 2004
Appl. No.:
10/813917
Inventors:
Steven G. Andres - Huntington Beach CA, US
David M. Cole - Santa Monica CA, US
Thomas Gregory Cummings - Laguna Niguel CA, US
Roberto Ramon Garcia - San Antonio TX, US
Brian Michael Kenyon - Aliso Viejo CA, US
George R. Kurtz - Coto de Caza CA, US
Stuart Cartier McClure - Ladera Ranch CA, US
Christopher William Moore - Huntington Beach CA, US
Michael J. O'Dea - Aliso Viejo CA, US
Ken D. Saruwatari - Laguna Niguel CA, US
Assignee:
McAfee, Inc. - Santa Clara CA
International Classification:
G06F 21/00
US Classification:
726 25, 726 23
Abstract:
A security risk management system comprises a vulnerability database, an asset database, a local threat intelligence database and a threat correlation module. The vulnerability database comprises data about security vulnerabilities of assets on a network gathered using active or passive vulnerability assessment techniques. The asset database comprises data concerning attributes of each asset. The threat correlation module receives threat intelligence alerts that identify attributes and vulnerabilities associated with security threats that affect classes of assets. The threat correlation module compares asset attributes and vulnerabilities with threat attributes and vulnerabilities and displays a list of assets that are affected by a particular threat. The list can be sorted according to a calculated risk score, allowing an administrator to prioritize preventive action and respond first to threats that affect higher risk assets. The security risk management system provides tools for performing preventive action and for tracking the success of preventive action.

System And Method Of Managing Network Security Risks

US Patent:
2012018, Jul 19, 2012
Filed:
Mar 28, 2012
Appl. No.:
13/432722
Inventors:
Steven G. Andres - Huntington Beach CA, US
David M. Cole - Santa Monica CA, US
Thomas Gregory Cummings - Laguna Niguel CA, US
Roberto Ramon Garcia - San Antonio TX, US
Brian Michael Kenyon - Aliso Viejo CA, US
George R. Kurtz - Coto de Caza CA, US
Stuart Cartier McClure - Ladera Ranch CA, US
Christopher William Moore - Huntington Beach CA, US
Michael J. O'Dea - Aliso Viejo CA, US
Ken D. Saruwatari - Laguna Niguel CA, US
International Classification:
G06F 21/00
US Classification:
726 25
Abstract:
A security risk management system comprises a vulnerability database, an asset database, a local threat intelligence database and a threat correlation module. The vulnerability database comprises data about security vulnerabilities of assets on a network gathered using active or passive vulnerability assessment techniques. The asset database comprises data concerning attributes of each asset. The threat correlation module receives threat intelligence alerts that identify attributes and vulnerabilities associated with security threats that affect classes of assets. The threat correlation module compares asset attributes and vulnerabilities with threat attributes and vulnerabilities and displays a list of assets that are affected by a particular threat. The list can be sorted according to a calculated risk score, allowing an administrator to prioritize preventive action and respond first to threats that affect higher risk assets. The security risk management system provides tools for performing preventive action and for tracking the success of preventive action.

Automated Systems And Methods For Generative Multimodel Multiclass Classification And Similarity Analysis Using Machine Learning

US Patent:
2018006, Mar 1, 2018
Filed:
Oct 20, 2017
Appl. No.:
15/789765
Inventors:
- Irvine CA, US
Stuart McClure - Irvine CA, US
Matthew Wolff - Laguna Niguel CA, US
Gary Golomb - Santa Cruz CA, US
Derek A. Soeder - Irvine CA, US
Seagen Levites - Portland OR, US
Michael O'Dea - Estero FL, US
Gabriel Acevedo - Irvine CA, US
Glenn Chisholm - Irvine CA, US
International Classification:
G06N 99/00
G06N 5/02
G06F 9/50
Abstract:
Under one aspect, a computer-implemented method includes receiving a query at a query interface about whether a computer file comprises malicious code. It is determined, using at least one machine learning sub model corresponding to a type of the computer file, whether the computer file comprises malicious code. Data characterizing the determination are provided to the query interface. Generating the sub model includes receiving computer files at a collection interface. Multiple sub populations of the computer files are generated based on respective types of the computer files, and random training and testing sets are generated from each of the sub populations. At least one sub model for each random training set is generated.

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