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Presentations Our work in our own words

November 13, 2019July 23, 2020

Scalable Infrastructure for Malware Labeling and Analysis

One of the best-known secrets of machine learning (ML) is that the most reliable way to get more accurate models […]

Konstantin Berlin
August 10, 2019July 23, 2020

Hacking Facial Recognition Systems

Facial recognition is becoming ubiquitous, but how it works is often confused with standard image classification.  In this short, high-level […]

Richard Harang
August 10, 2019July 23, 2020

Loss is More! Improving Malware Detectors by Learning Additional Tasks

Malware detection is perhaps the most common use case of machine learning for information security (ML-Sec/AI-Sec). ML-Sec malware detectors consist […]

Ethan Rudd
August 7, 2019July 23, 2020

Security data science – Getting the fundamental right

https://www.youtube.com/watch?v=XfT0Ju4vhvI&t=1254 A data science team is now table stakes for most security operations, however data science for security poses unique […]

Richard Harang
October 18, 2018July 23, 2020

Some Mistakes are More Mistaken Than Others: Using Cost-Matrix Clustering to Address Misclassification Cost Asymmetries in Website Content Classification

Website content classification has several salient characteristics as a machine learning problem, but perhaps the most salient is that it […]

Cody Wild
October 13, 2018July 23, 2020

Estimating Uncertainty for Binary Classifiers

In practical applications of binary classification, knowing the uncertainty of the prediction can be almost as important as knowing the […]

Richard Harang
August 9, 2018June 22, 2020

AI DevOps: Behind the Scenes of a Global AV’s Machine Learning Infrastrcture

Alex Long
August 8, 2018July 23, 2020

Measuring the Speed of the Red Queen’s Race; Adaption and Evasion in Malware

Security is a constant cat-and-mouse game between those trying to keep abreast of and detect novel malware, and the authors […]

Richard Harang
Felipe Ducau
August 7, 2018July 23, 2020

An Introduction to Machine Learning and Deep Learning

Machine learning is the science of developing programs that can automatically learn from data. First, this talk will give some […]

Hillary Sanders
July 26, 2017July 23, 2020

Garbage In, Garbage Out: How Purportedly Great Machine Learning Models can be Screwed Up by Bad Data

As processing power and deep learning techniques have improved, deep learning has become a powerful tool to detect and classify […]

Hillary Sanders

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