Intuit, Inc.

Capen Brinkley

Luis Felipe Cabrera

M Shannon Lietz

Thomas Bishop

Brett Weaver

Javier Godinez

Christian Price

Shannon M Lietz

Big data analysis methods and machine learning based models are used to provide offer recommendations to consumers that are probabilistically determined to be relevant to a given consumer. Machine learning based matching of user attributes and offer attributes is first performed to identify potentially relevant offers for a given consumer. A de-duplication process is then used to identify and eliminate any offers represented in the offer data that the consumer has already seen, has historically shown no interest in, has already accepted, that are directed to product or service types the user/consumer already owns, for which the user does not qualify, or that are otherwise deemed to be irrelevant to the consumer.

Replacing a potentially threatening virtual asset

A method and system include identifying a virtual asset creation template associated with virtual assets to be verified. A test virtual asset is generated using the virtual asset creation template and deployed in a testing environment. The test virtual asset is then analyzed in the testing environment to identify any vulnerabilities. If a vulnerability is identified in the designated test virtual asset, a remedy to the vulnerability is applied to the virtual asset creation template which is used to create a virtual asset in a production environment. The method and system further include monitoring the production environment virtual asset for potential security threats, with a virtual asset agent, and determining a severity of identified security threats. and potentially creating a new virtual asset with the virtual asset agent and decommissioning the current virtual asset as a result.

Method and system for creating and deploying virtual assets

A method and system for protecting and repairing a current virtual asset from damage by potential security threats, according to one embodiment. The method and system include monitoring a current a current virtual asset for potential security threats, with a virtual asset agent, according to one embodiment. The method and system include determining a severity of the potential security threats that are identified by the virtual asset agent, according to one embodiment. The method and system include creating a new virtual asset with the virtual asset agent and decommissioning the current virtual asset, according to one embodiment. The system and method receiving, with the new virtual asset, secrets that are associated with the current virtual asset to enable the new virtual asset to continue operations of the current virtual asset, according to one embodiment.

Method and system for secure delivery of information to computing environments

An application is implemented in the production environment in which the application will be used. Two or more backend systems are used to implement different versions of the application using the production environment in which the application will actually be used and accessed. Actual user data is received. A first portion of the actual user data is routed and processed in the production environment using a first version of the application and a first backend system of the two or more backend systems. A second portion of the actual user data is also routed and processed in the production environment but using a second version of the application and a second backend system of the two or more backend systems. The results data is then analyzed to evaluate the various versions of the application in the production environment.

Method and system for comparing different versions of a cloud based application in a production environment using segregated backend systems

Asset security compliance data ensuring defined asset security policies are applied to the creation and/or operation of assets to be used to implement an application and application deployment security compliance data for ensuring compliance with one or more application deployment security policies associated with the deployment of assets used to implement the application is generated. The asset security compliance data is then used to ensure each asset used to implement the application is created and used in compliance with asset security policies and the application deployment security compliance data is used to ensure that each asset used to implement the application is deployed in compliance with the application deployment security policies.

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San Diego, CA, United States of America

Capen Brinkley