Abstract: Systems and methods for training an agent-based assistant model are provided. In embodiments, a method includes: obtaining biometric data of a user from a software application utilizing an assistant model that determines functions of the software application; filtering the biometric data based on predetermined categories, thereby extracting select biometric data; training a first version of the assistant model based on the select biometric data, thereby generating an updated assistant model; generating a summary of changes including changes to the first version of the assistant model that occurred during the training; and sending the summary of changes to a remote federated learning server, wherein the federated learning server trains a general version of the assistant model based on the summary of changes and other summary of changes received from computing devices of other users, thereby generating an updated general version of the assistant model.

Abstract: Methods and systems for artificially intelligent security incident and event management using an attention-based deep neural network and transfer learning are disclosed. A method includes: collecting, by a computing device, system and network activity events in bulk; forming, by the computing device, a corpus using the collected system and network activity events; correlating, by the computing device, discrete events of the system and network activity events into offenses; adding, by the computing device, additional features to the corpus representing the offenses and disposition decisions regarding the offenses; training, by the computing device, a deep neural network using the corpus; and tuning, by the computing device, the deep neural network for a monitored computing environment using transfer learning.