Advances in Machine Learning for Cyber Defense

pdf

ABSTRACT
Picking an attacker’s signals out of billions of log events in near real time from petabyte scale storage is a daunting task, but Microsoft has been using security data science at cloud scale to successfully disrupt attackers. This session will present the latest frameworks, techniques and the machine-learning algorithms that Microsoft uses to protect its infrastructure and customers.

Ram Shankar is a Data Cowboy at the Azure Security Data Science team at Microsoft, where his team's primary focus is modeling massive amounts of security logs to surface malicious activity. His work has appeared in industry conferences like Defcon, BSides, BlueHat, DerbyCon, MIRCon, Infiltrate, Strata+Hadoop World as well as academic conferences like NIPS and ACM-CCS. Ram graduated from Carnegie Mellon University focusing on machine learning and security.
 

Tags:
License: CC-2.5
Submitted by Katie Dey on