Assessment of machine learning methods for intruder detection in industrial control networks

Cybersecurity is a matter of paramount importance to industrial control systems. There is an increasing possibility that industrial control systems may be the subject of cyber attacks, causing severe consequences. Menya is exploring the possibility to develop a solution that mainly aims at protecting the security of industrial control networks and bus technologies used in the aerospace and space industry. The intern will analyze data related to a specific industrial control network to assess the potential that the data canbe exploited to train machine learning models to detection intruders in such networks. This assessment will provide recommendations with respect to the quality of data, additional data that might need to be collected, and potential machine learning models that could be used.

D’Jeff Kanda Nkashama
Superviseur universitaire: 
Marc Frappier
Partner University: