Fti Consulting, Inc.

Domain Tools, LLC

Domain Tools Holdings, LLC

John W Conwell

William C Knight

Nicholas I Nussbaum

Sean M McNee

Methods, systems, and techniques for producing and using enhanced machine learning models and computer-implemented tools to investigate cybersecurity related data and threat intelligence data are provided. Example embodiments provide an Enhanced Predictive Security System, for building, deploying, and managing applications for evaluating threat intelligence data that can predict malicious domains associated with bad actors before the domains are known to be malicious. In one example, the EPSS comprises one or more components that work together to provide an architecture and a framework for building and deploying cybersecurity threat analysis application, including machine learning algorithms, feature class engines, tuning systems, ensemble classifier engines, and validation and testing engines. These components cooperate and act upon domain data and feature class vectors to create sampled test, training, and validation data and to build model subsets and applications using a trained model library, which stores definitions of each model subset for easy re-instantiation.

Multi-level ensemble classifiers for cybersecurity machine learning applications

Enhanced neutral domain data selection for cybersecurity machine learning applications

A system and method for displaying relationships between concepts to provide classification suggestions via injection is provided. A reference set of concepts each associated with a classification code is designated. Clusters of uncoded concepts are designated. One or more of the uncoded concepts from at least one cluster are compared to the reference set. At least one of the concepts in the reference set that is similar to the one or more uncoded concepts is identified. The similar concepts are injected into the at least one cluster. Relationships between the uncoded concepts and the similar concepts in the at least one cluster are visually depicted as suggestions for classifying the uncoded concepts.

System and method for displaying relationships between concepts to provide classification suggestions via injection

A system and for displaying relationships between concepts to provide classification suggestions via inclusion is provided. A set of reference concepts each associated with a classification code is designated. One or more of the reference concepts are combined with a set of uncoded concepts. Clusters of the uncoded concepts and the one or more reference concepts are generated. Relationships between the uncoded concepts and the one or more reference concepts in at least one cluster are visually depicted as suggestions for classifying the uncoded concepts in that cluster.

System and method for displaying relationships between concepts to provide classification suggestions via inclusion

A system and method for displaying relationships between concepts to provide classification suggestions via nearest neighbor is provided. Reference concepts previously classified and a set of uncoded concepts are provided. At least one uncoded concept is compared with the reference concepts. One or more of the reference concepts that are similar to the at least one uncoded concept are identified. Relationships between the at least one uncoded concept and the similar reference concept are depicted on a display for classifying the at least one uncoded concept.

System and method for displaying relationships between concepts to provide classification suggestions via nearest neighbor

A system and method for providing generating reference sets for use during document review is provided. A collection of unclassified documents is obtained. Selection criteria are applied to the document collection and those unclassified documents that satisfy the selection criteria are selected as reference set candidates. A classification code is assigned to each reference set candidate. A reference set is formed from the classified reference set candidates. The reference set is quality controlled and shared between one or more users.

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Tukwila, WA, United States of America

John W Conwell