Crowdstrike, Inc.

Nference, Inc.

Tyler Feener

Tyler Wagner

Lorenzo Kogler Anele

Tanya Widen

Stefan Stein

Danylo Oliynyk

Eric Brine

Arnaud Wald

Bharathwaj Raghunathan

Shimeng Chen

Eric Loui

Vishal Jain

Rashik Shahjahan

A system and method of detecting malicious activity in emails using pattern recognition. The method includes maintaining a plurality of associations between a plurality of emails and a plurality of multi-dimensional (MD) vectors of the plurality of emails. Each association is between a respective email of the plurality of emails and a respective MD vector of the plurality of MD vectors that corresponds to the respective email. The method includes identifying, based on one or more keywords, a set of MD vectors of the plurality of MD vectors. The method includes selecting, based on the plurality of associations, a set of emails associated with the set of MD vectors. The method includes generating, by a processing device, based on the set of emails or the set of MD vectors, a set of clusters to represent patterns in the set of emails.

Identifying patterns in large quantities of collected emails

Disclosed herein are methods for identifying and classifying relationships between entities. A method of identifying relationships includes receiving a first entity and a second entity; accessing a corpus; retrieving a plurality of sentences containing the first entity and the second entity from the corpus; identifying a plurality of relational phrases by extracting a relational phrase from each of the plurality of sentences; and identifying one or more relationships between the first entity and the second entity. A method of classifying relationships includes using a classification model.

Method and system for determining relationships between linguistic entities

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Toronto, Canada

Tyler Feener