Online: Malware Detection, Enabled by Machine Learning

As malware becomes more sophisticated, new machine learning techniques and tools are needed in order to keep pace. Join us for our first talk of 2021 to learn how analysts can be kept informed through an automated machine learning process.

Agenda

12:00 PM -- Greetings

12:05 PM -- Malware Detection, Enabled by Machine Learning - Tina Coleman

01:30 PM -- Closings

Location

Zoom and YouTube Streaming
A link will be sent out prior to the event. Please note that Zoom is capped at 100, so if you do not get into Zoom, you will be able to watch via YouTube.

Talks

Malware Detection, Enabled by Machine Learning
With the scale of new malware being created each year growing, as well as the expanding market opportunities for malware reuse, protecting systems can’t rely solely on downloading a vendor’s updated virus signature files. Our customers need ways to detect and cordon likely threats, by using data retrieved from a combination of static and behavioral characteristics, and comparing it to other classes of “good” versus “bad” files. Optimally, the solution cordons risky files, force ranks them according to their likelihood of causing harm, correlates some metadata to help with further learning and to provide context to analysts, and lets an analyst “release” a file after further analysis and a request from a user. Oh, with that feedback relayed back into the model to support further tuning.

This talk will delve into IRAD efforts ClearEdge is doing on building and integrating malware detectors using machine learning algorithms.

Speakers

Tina Coleman is a Technical Director for ClearEdge. In that role, she’s accountable for furthering the company’s depth in cybersecurity, particularly in aspects that allow ClearEdge to build solutions that scale for customer needs using its strengths in software engineering, dev ops, and data science. In addition to her work on contract and as a Technical Director, Ms. Coleman leads the Women In Technology program for ClearEdge, which seeks to encourage the participation and retention of women in technology. Ms. Coleman graduated from UMBC with undergraduate degrees in Computer Science and Economics and is currently pursuing her Masters in Cybersecurity Technology from University of Maryland, Global Campus. Tina can be found on LinkedIn at https://www.linkedin.com/in/tinadcoleman/