COMPUTATIONAL RESEARCH AND APPLICATIONS SEMINAR – Detecting Automated and Coordinated Activity in Cyber Logs at Scale – Deason
COMPUTATIONAL RESEARCH AND APPLICATIONS SEMINAR
Lauren Deason, PhD
Lead Data Scientist
Punch Cyber Analytics Group
Monday, September 25, 4:30-5:45
Exploratory Hall, Room 3301
ABSTRACT: This presentation will detail novel analytic methods for processing time series data at scale using techniques drawn from digital signal processing and document matching. These methods can be applied to detect coordinated and automated cyber activity, to match patterns present in time series data, and to fuse together disparate datasets.
Dr. Deason holds a BS in Applied Mathematics from the University of Virginia, a MA in Mathematics with an emphasis in Real Analysis and Probability Theory from UC Berkeley, and a PhD in Economics from the University of Maryland, College Park. Dr. Deason has 10 years of experience in mathematical modeling and data science, spanning employment as a Professor of Mathematics, an Economist, and a Data Scientist. Dr. Deason’s past experience includes developing dynamic stochastic models within a game theoretic framework to explore the effects of trade policy uncertainty as well as estimating empirical models to explain various phenomena. More recently, Dr. Deason has developed multiple algorithms for detecting and classifying periodic and coordinated behavior in a variety of contexts on large data sets as part of DARPA’s Network Defense Program.