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Presentations Our work in our own words

July 31, 2021December 5, 2022

BSides LV 2021: Bad Neighborhoods – data-driven detection of malicious internet infrastructure

Tamás Vörös
August 9, 2020August 12, 2020

DEF CON 28 AI Village: Detecting hand-crafted social engineering emails with a bleeding-edge neural language model

Joshua Saxe
Younghoo Lee
June 10, 2020July 23, 2020

Learning from Context: A Multi-view Deep Learning Architecture for Malware Detection

Machine learning (ML) used for static portable executable (PE) malware detection typically employs per-file numerical feature vector representations as input […]

Adarsh Kyadige
Ethan Rudd
Konstantin Berlin
May 9, 2020June 23, 2020

Describing Malware via Tagging

Although powerful for conviction of malicious artifacts, machine learning based detection do not generally produce further information about the type […]

Felipe Ducau
Konstantin Berlin
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

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