Abstract: Described herein is a system and method for utilizing data flow analysis to perform data classification with respect to a source dataset and a generated derived dataset. A flow confidence for a field is calculated using an adaptive algorithm in accordance with the action performed and the derived dataset. An associated derived confidence for a particular tag is calculated in accordance with an associated confidence and the flow confidence. When the associated derived confidence is greater than or equal to a first threshold, the particular tag is copied to the derived dataset. In some embodiments, when the associated derived confidence is less than or equal to a second threshold, the particular tag is not copied to the derived dataset. Otherwise an action to be taken is identified. A response to the action is received and the adaptive algorithm is modified in accordance with the received response.

Abstract: According to one aspect of the present disclosure, a computing device is provided, including non-volatile memory storing a database including a plurality of database entries. The computing device may further include a processor configured to sort the plurality of database entries into a plurality of database entry length sets. For each database entry length set, each database entry included in the database entry length set may be within a predefined length range. For each database entry length set, the processor may be further configured to generate a probabilistic data structure based on the one or more database entries included in the database entry length set.

Abstract: Described herein is a system and method for utilizing data flow analysis to perform data classification with respect to a source dataset and a generated derived dataset. A flow confidence for a field is calculated using an adaptive algorithm in accordance with the action performed and the derived dataset. An associated derived confidence for a particular tag is calculated in accordance with an associated confidence and the flow confidence. When the associated derived confidence is greater than or equal to a first threshold, the particular tag is copied to the derived dataset. In some embodiments, when the associated derived confidence is less than or equal to a second threshold, the particular tag is not copied to the derived dataset. Otherwise an action to be taken is identified. A response to the action is received and the adaptive algorithm is modified in accordance with the received response.

Abstract: According to one aspect of the present disclosure, a computing device is provided, including non-volatile memory storing a database including a plurality of database entries. The computing device may further include a processor configured to sort the plurality of database entries into a plurality of database entry length sets. For each database entry length set, each database entry included in the database entry length set may be within a predefined length range. For each database entry length set, the processor may be further configured to generate a probabilistic data structure based on the one or more database entries included in the database entry length set.