Abstract: Embodiments of the present disclosure provide systems and methods for matching data entities across disparate datasets. One method may include generating a reference numeric vector for a reference data object and generating a plurality of match candidate numeric vectors for a plurality of match candidate data objects. The method may also include identifying a subset of match candidate data objects from the plurality of match candidate data objects and generating a plurality of data features based on a comparison between one or more reference object attributes corresponding to the reference data object and one or more matching object attributes corresponding to the subset of match candidate data objects. The method may also include identifying a match between the reference data object and a match candidate data object of the subset of match candidate data objects based on the plurality of data features.

Abstract: Various embodiments of the present disclosure provide a feature engineering framework for generating task-specific contextual embeddings to improve machine learning model performance, while reducing memory requirements for the performance of a predictive task. The techniques may include identifying a plurality of entity predictive identifiers from historical data objects for an entity. The entity predictive identifiers are used with a task-specific data store to generate a textual entity document for the entity by concatenating a set of contextual text descriptions from the task-specific data store that correspond to a set of task relevant identifiers from the plurality of entity predictive identifiers. The techniques include generating, using a machine learning encoder model, a contextual entity embedding for the entity based on the textual entity document and then training, using the contextual entity embedding, a machine learning classification model for the performance of the predictive task.

Abstract: Embodiments of the present disclosure provide systems and methods for matching data entities across disparate datasets. One method may include generating a reference numeric vector for a reference data object and generating a plurality of match candidate numeric vectors for a plurality of match candidate data objects. The method may also include identifying a subset of match candidate data objects from the plurality of match candidate data objects and generating a plurality of data features based on a comparison between one or more reference object attributes corresponding to the reference data object and one or more matching object attributes corresponding to the subset of match candidate data objects. The method may also include identifying a match between the reference data object and a match candidate data object of the subset of match candidate data objects based on the plurality of data features.

Abstract: The disclosure includes a method that includes receiving network traffic having a first plurality of packets that each indicate a first packet source and a first packet destination; determining an analysis host destination for each of the first plurality of packets such that the packets are distributed among a plurality of analysis hosts with communications between a given source-destination pair being sent to the same analysis host; encapsulating the first plurality of packets to generate a second plurality of encapsulated packets having the first plurality of packets as a second packet payload; and sending the second plurality of encapsulated packets to respective analysis host destinations.

Abstract: The disclosure includes a method that includes receiving network traffic having a first plurality of packets that each indicate a first packet source and a first packet destination; determining an analysis host destination for each of the first plurality of packets such that the packets are distributed among a plurality of analysis hosts with communications between a given source-destination pair being sent to the same analysis host; encapsulating the first plurality of packets to generate a second plurality of encapsulated packets having the first plurality of packets as a second packet payload; and sending the second plurality of encapsulated packets to respective analysis host destinations.

Abstract: A delivery verification service receives an electronic message that indicates delivery of an authentication device. In response to receiving the electronic message, the delivery verification service identifies, based at least in part on the electronic message, a set of attributes of a recipient to which the authentication device was delivered. Based at least in part on these attributes of the recipient, the delivery verification service determines whether to activate the authentication device. If the delivery verification service determines that the authentication device can be activated, the delivery verification service causes the authentication device to be enabled.