This event has ended. Visit the official site or create your own event on Sched.
Tom Tom champions civic innovation, creativity, and entrepreneurship in America’s hometowns.

[Back to Tom Tom Festival]
Back To Schedule
Thursday, April 11 • 1:05pm - 1:35pm
Detecting The Unknown: Using Unsupervised Behavior Models To Expose Malicious Network Activity

Log in to save this to your schedule, view media, leave feedback and see who's attending!

Feedback form is now closed.
We'll describe our work to achieve anomaly detection at network speed by combining probabilistic modeling, graph-based models, and more traditional machine learning techniques with the open source RAPIDS suite of software libraries. Traditional approaches to cybersecurity take a reactive approach, studying previous attacks to flag similar attacks in the future. This leaves systems vulnerable to day zero attacks in which adversaries use entirely new tactics to infiltrate a network. We'll explain how we address this issue by using multiple unsupervised models to alert cyber analysts about anomalous behavior, and then incorporate analysts' feedback to continuously update our models. The nature of anomaly detection in this low signal-to-noise space results in a high-false positive rate for most machine learning approaches. To mitigate this, we incorporate cyber analysts' feedback on alerts to continuously update our models. By combining the power of machine learning with experts' cyber knowledge in one integrated learning platform powered by GPUs, we improve the accuracy of future alerts, overall model performance, and reduce the time to detection for novel attacks. 

You need this ticket from Eventbrite to sign up: Applied Machine Learning Conference.

avatar for Will Badart

Will Badart

Machine Learning Engineer, Booz Allen Hamilton
Will is a web developer turned software engineer turned data scientist at Booz Allen Hamilton. At Booz Allen, Will designs and builds novel, AI-driven cyber defenses and systems to deliver them. Will has a passion for design, vim, martial arts, and open source software.
avatar for Sarah Olson

Sarah Olson

Data Scientist, Booz Allen Hamilton
Sarah Olson is a Data Scientist at Booz Allen Hamilton, with current focus areas in cyber security, machine learning models, and natural language processing. Her projects at the company have supported a variety of her interests, ranging from developing models to detect credential... Read More →


Thursday April 11, 2019 1:05pm - 1:35pm EDT
Violet Crown: Theater 2