Lateral movement is a typical tactic in a multi-stage cyber attack. In this interactive discussion, we'll look at how to accelerate the speed and accuracy of lateral movement detection — through a use case based approach.
In this webinar recording, featuring from data scientist Adrian Sarno, you'll learn:
Adrian Sarno, PatternEx data scientist, focuses on creating models to estimate the probability of a variety of Cyber Security attacks. For the last year, Adrian's role has involved researching attack patterns, designing data representations, developing datasets, coding pipelines in Scala and developing Machine Learning models in Python with SciKit-Learn, Keras and TensorFlow.
Adrian started his career at Microsoft, as software developer in the Windows team designing data analytics modules. He later moved to Ericsson to participate in the development of InfoSec projects in cooperation with the corporate security team. More recently Adrian ventured into the startup scene, joining the Data Science team at Corax Cyber before joining PatternEx in 2017. Adrian Sarno holds a BSc in Computer Science from University of Buenos Aires and a Masters from Trinity College Dublin (Ireland).