Capital One Services, LLC

Steven Lott

Philip Austin Kedy

Brian Lee Wong

Virendra K Abelak

Embodiments disclosed are directed to ensuring resource compliance within a cloud-based environment. The embodiments include steps for performing both pre-provisioning and post-provisioning checks of resources, such as network protocols, prior to and after their deployment within the cloud-based environment. These steps include using bitemporal analysis to determine the impact of deploying resources within the environment through the use of multiple execution timelines where the impact of deploying a resource may be evaluated on an alternative timeline that does not change the current resource scope of the cloud-based environment. The analysis may further include tracking the impact of the resource after it has been deployed to ensure resource compliance.

Managing pre-provisioning and post-provisioning of resources using bitemporal analysis

Embodiments disclosed are directed to ensuring resource compliance within a cloud-based environment. The embodiments include steps for performing pre-provisioning checks of resources, such as network protocols, prior to their deployment within the cloud-based environment. These steps include using bitemporal analysis to determine the impact of deploying resources within the environment through the use of multiple execution timelines where the impact of deploying a resource may be evaluated on an alternative timeline that does not change the current resource scope of the cloud-based environment.

Managing pre-provisioning of resources using bitemporal analysis

Embodiments disclosed are directed to ensuring resource compliance within a cloud-based environment using a compliance system. The embodiments include steps for performing pre-provisioning checks of resources, such as network protocols, prior to their deployment within the cloud-based environment. The compliance system may include a number of components for performing the pre-provisioning check including a maintenance module, a collection module, and an evaluation module, which are used to evaluate the resource prior to deployment in the cloud-based environment.

Resource compliance system using bitemporal analysis

A system, method, and computer-readable medium for generating synthetic data are described. Improved data models for databases may be achieved by improving the quality of synthetic data upon for modeling those databases. According to some aspects, these and other benefits may be achieved by using numeric distribution information in a schema describing one or more numeric fields and, based on that schema, distribution-appropriate numerical data may be generated. The schema may be compared against actual data and the schema adjusted to more closely match the actual data. In implementation, this may be effected by storing a schema with distribution information and/or one or more parameters, generating synthetic numerical data based on the schema, and, based on a comparison with actual data, modify the schema until the synthetic data is statistically similar to the actual data. A benefit may include improved database performance and indexing based on repeatable, statistically appropriate, synthetic data.

Schema validation with data synthesis

A system, method, and computer-readable medium for generating synthetic data are described. Improved data models for databases may be achieved by improving the quality of synthetic data upon for modeling those databases and for checking the authenticity of existing numerical data. According to some aspects, these and other benefits may be achieved by using numeric distribution information in a schema describing one or more numeric fields and, based on that schema, distribution-appropriate numerical data may be generated. Also, another schema may be used to generate a second set of numerical data having a different distribution that is not expected for the one or more numeric fields. Actual data may be compared against the generated datasets. When the actual data is determined to be statistically similar to the second numerical dataset, an alert may be generated. A benefit includes finding potentially fraudulent datasets using an efficient approach.

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McLean, VA, United States of America

Steven Lott