Managing data in a cybersecurity context: networking, database, machine learning. Understanding the link between performance and security in various contexts.
The student is expected to
- Better understand the context and reasons that lead to existing attacks against service availability, and existing defenses.
- Better understand how to handle data. How to safely expose them, and what limit existing techniques have.
- Undestanding the difference between machine learning applied to computer security versus computer security applied to machine learning.
- Gaining knowledge on Pervasive Monitoring (Mass surveillance), and how to defend against it.
- Understanding the intrication between the performance and security of the Web.
The course covers and studies the performance and security of systems in which
a lot of data is managed. It ranges from company networks expecting to
establish a secure architecture handling Gb/s of traffic, to safely exposing
data online while ensuring modern security definitions for privacy. The course
also contains alternative directions to the existing Internet architecture, and
compare benefits and issues. Among them, Onion services and cesorship resistance
We will also explore machine learning applied to detection intrusion, and cover
the pitfalls.
The course evaluation will be based either:
- on the project, on participation in the class, and on the quality of the material given in the inverted classes.
- on the project and on a written or oral examination in session.