Abstract: Disclosed are various embodiments for augmented intelligent machine for systematic attribution of data security. A set of global regulations is received by the system. Next, at least one decision rule for mapping one or more data elements is output based at least in part on the set of dynamic global regulations. A data input is received from at least one data source. Next, the data input is parsed to determine at least one sensitive data elements. Then, a confidentiality level of at least one sensitive data element is determined. The ingesting table is joined with a drive mapping data set. Finally, at least one security policy is applied to a type of data input based at least in part on the drive mapping data set or the confidentiality level.

Abstract: Disclosed are various embodiments for configurable and event driven smart hybrid cloud orchestrators. Various embodiments include a first computing device that can receive a request that includes various configurations to perform one or more actions. The first computing device can generate machine-readable instructions to perform a first action. The first computing device can send a first event to an event hub that includes the machine-readable instructions. The second computing device can receive the first event from the event hub and provision computing resources. The second computing device can then modify the machine-readable instructions based on the computing resources and then execute the machine-readable instructions. The second computing device can send a second event indicating that the first action has completed. The first computing device can receive the second event from the event hub.

Abstract: Disclosed are various embodiments for augmented intelligent machine for systematic attribution of data security. A set of global regulations is received by the system. Next, at least one decision rule for mapping one or more data elements is output based at least in part on the set of dynamic global regulations. A data input is received from at least one data source. Next, the data input is parsed to determine at least one sensitive data elements. Then, a confidentiality level of at least one sensitive data element is determined. The ingesting table is joined with a drive mapping data set. Finally, at least one security policy is applied to a type of data input based at least in part on the drive mapping data set or the confidentiality level.

Abstract: The method includes receiving a data file comprising a record; identifying a characteristic of the record; appending a characteristic marker to the record reflecting the characteristic; receiving a data request from a user; identifying a clearance identifier associated with the user, wherein the clearance identifier indicates whether the user has clearance to access the record based on the characteristic of the record; retrieving the record in response to the receiving the data request; comparing the characteristic marker of the record with the clearance identifier; and/or determining whether the user has clearance to access the record.

Abstract: Systems and methods of securely storing and retrieving data are disclosed. A database may include a table of data with rows and columns and encrypted at rest. The data may be desired to be accessed by users. However, each user may have different access permissions and each row or column may have different characteristics, such as encryption, data type, and/or the like. As such, access to the data may be controlled in according to the characteristics of the data, the access permissions of the user, and/or the encryption of the data.

Abstract: A system for monitoring data-access behavior is provided. The system may derive a behavioral pattern based on at least one of historic data access by a user or expected data access by the user. The system may also generate a behavioral model for the user based on the behavioral pattern for the user. In response to detecting a data access activity by the user, the system may compare the data access activity to the behavioral model to determine the data access activity is unusual for the user. The system may further trigger a remediation action in response to determining the data access activity is unusual for the user.

Abstract: Systems and methods of securely storing and retrieving data are disclosed. A database may include a table of data with rows and columns and encrypted at rest. The data may be desired to be accessed by users. However, each user may have different access permissions and each row or column may have different characteristics, such as encryption, data type, and/or the like. As such, access to the data may be controlled in according to the characteristics of the data, the access permissions of the user, and/or the encryption of the data.

Abstract: Systems and methods of securely storing and retrieving data are disclosed. A database may include a table of data with rows and columns and encrypted at rest. The data may be desired to be accessed by users. However, each user may have different access permissions and each row or column may have different characteristics, such as encryption, data type, and/or the like. As such, access to the data may be controlled in according to the characteristics of the data, the access permissions of the user, and/or the encryption of the data.

Abstract: Systems and methods of securely storing and retrieving data are disclosed. A database may include a table of data with rows and columns and encrypted at rest. The data may be desired to be accessed by users. However, each user may have different access permissions and each row or column may have different characteristics, such as encryption, data type, and/or the like. As such, access to the data may be controlled in according to the characteristics of the data, the access permissions of the user, and/or the encryption of the data.