Feb 25 2020 - Machine Learning applied to Cyber Security … This time it’s different?

 

Machine learning has gained a lot of hype and has become a buzz word in the last couple of years, and purports to solve many of the challenges facing the cyber security community. However, there has been many hype cycles that have never delivered. This presentation will cover what recent advances has occurred in Machine Learning, what do these advances mean to the cyber security community, what changes need to be made to cyber risk assessments, how can one “hack” Machine Learning algorithms and what are the geopolitical events that could drive the direction and funding of Machine Learning in the foreseeable future.

 

 

Major James Lindsay spent the first part of his career in the Petawawa area, building and securing field deployable tactical computer networks and holding multiple key positions at the brigade level. In 2008 Maj. Lindsay deployed to Kandahar Afghanistan and commanded 72 solders, which were in charge of all the Canadian Communication Infrastructure, with the Afghanistan theatre.

In 2011, Maj. Lindsay was posted to the National Capital Region as a Senior IT Security Engineer, and has worked his way up to become the Chief Architect and Engineer of End Point security for the Department of National Defence (DND). His previous job was the Chief Architect and Engineer for IT Risk Assessment for DND. His secondary duty is advising the Senior Management of DND on how to implement AI into cyber applications.

Maj. Lindsay holds an undergraduate degree in Computer Science and a masters in Electrical Engineering. While at the Royal Military College (RMC), Maj. Lindsay received the Col. Geoff Parker award and the IEEE master research award for the Kingston area in 2011. His masters’ work focused on using Artificial Intelligence (AI) techniques on cooperative control problems. On his own time, Maj. Lindsay is currently pursuing a part time PhD in Computer Engineering that focuses on deep Reinforcement Learning techniques applied to anonymous robotics. He currently has 6 peer reviewed academic publications that covers multiple areas of machine learning and AI.