Build Better Defenses
October 29–30, 2017: Training
October 30–November 1, 2017: Tutorials & Conference
New York, NY

TRAINING: Data analysis and machine learning for cybersecurity

Charles Givre (Deutsche Bank), Jay Jacobs (BitSight Technologies)
9:00am–5:00pm Monday, October 30, 2017
Location: Madison

Who is this presentation for?

  • You're a security professional who needs to parse and interpret data more effectively and efficiently.

Prerequisite knowledge

  • A working knowledge of a scripting or programming language (ideally Python or R)
  • Familiarity with security data sources, including vulnerability scanner data, DNS data, and threat intelligence data
  • Recommended preparation: Python for Data Analysis by Wes McKinney

What you'll learn

  • Understand how to organize and execute a data analysis project, from exploration to insight
  • Gain experience working with different data formats
  • Learn how the science of data visualization can transform how you communicate your story
  • Explore the applications of models and machine learning techniques
  • Evaluate the effectiveness of your model


Join experts Jay Jacobs and Charles Givre for an in-depth exploration of data analysis and machine learning in cybersecurity. You’ll learn how to explore and analyze data you probably already have and gain valuable exposure to and experience with tools and techniques to prepare, analyze, and visualize the knowledge hiding in your data. Jay and Charles guide you through working with three hands-on, practical applications with real data, introducing each with a language-agnostic approach before providing language-specific guidance for hands-on work. A GitHub repository with the examples will be available so that you can revisit the examples and continue learning after the training.

Photo of Charles Givre

Charles Givre

Deutsche Bank

Charles Givre is an unapologetic data geek who is passionate about helping others learn about data science and become passionate about it themselves. For the last five years, Charles has worked as a data scientist at Booz Allen Hamilton for various government clients and has done some really neat data science work along the way, hopefully saving US taxpayers some money. Most of his work has been in developing meaningful metrics to assess how well the workforce is performing. For the last two years, Charles has been part of the management team for one of Booze Allen Hamilton’s largest analytic contracts, where he was tasked with increasing the amount of data science on the contract—both in terms of tasks and people.

Even more than the data science work, Charles loves learning about and teaching new technologies and techniques. He has been instrumental in bringing Python scripting to both his government clients and the analytic workforce and has developed a 40-hour Introduction to Analytic Scripting class for that purpose. Additionally, Charles has developed a 60-hour Fundamentals of Data Science class, which he has taught to Booz Allen staff, government civilians, and US military personnel around the world. Charles has a master’s degree from Brandeis University, two bachelor’s degrees from the University of Arizona, and various IT security certifications. In his nonexistent spare time, he plays trombone, spends time with his family, and works on restoring British sports cars.

Photo of Jay Jacobs

Jay Jacobs

BitSight Technologies

Jay Jacobs is the senior data scientist at BitSight Technologies. Previously, Jay spent four years as the lead data analyst for the Verizon Data Breach Investigations Report. Jay is the coauthor of Data-Driven Security, which covers data analysis and visualizations for information security, and hosts the Data-Driven Security and R World News podcast. Jay is also a cofounder of the Society of Information Risk Analysts and currently serves on its board of directors. Jay is active in the R community; he coordinates his local R user group for the greater Minneapolis area and contributes to local events and functions supporting data analysis.