AI for Cybersecurity

Course guarantor:

Tomáš Pevný

Lecturer:

Sebastián García, Tomáš Pevný

Tutor:

Sebastián García, Tomáš Pevný

Supervisor:

Department of Computer Science

Synopsis:

The goal of the course is to learn about cybersecurity and the importance of using AI in this field to understand how it transforms our perception of security in general.

Requirements:

Syllabus of lectures:

Introduction to the class, security and networking

Finding computers, scan and basic network analysis

Gaining access. From people to computers

Detecting Intruders to your servers

Honeypots

Persistence&Priviledge escalation, Side channel attacks

Buffer overflow

Reverse Engineering

Automating Attacks with Malware

Manual and machine learning detection of C&C

Web Attacks

Mobile Security, NOC

Syllabus of tutorials:

Study Objective:

The goal of the course is to learn about cybersecurity and the importance of using AI in this field to understand how it transforms our perception of security in general. In particular:

. To learn the whole cybersecurity ecosystem in the modern AI era.

. To learn how to attack and how to defend in real situations.

. To learn how to protect systems against cybersecurity attacks.

. To learn how to attack systems in order to understand them.

. To learn that cybersecurity is not the same as before given the new technology of AI applied to the field.

. To learn how to defend against attacks using AI to cybersecurity systems, defend against attacks to AI systems, all by learning how to better attack them.

Study materials:

Artificial Intelligence in Cybersecurity: Revolutionize Cybersecurity with AI, Dr. Anjum Zameer Bhat , Dr. Narayana Swamy Ramaiah, ISBN-13: 979-8322233589, 2024

The AI Revolution in Networking, Cybersecurity, and Emerging Technologies, Omar Santos, Samer Salam, Hazim Dahir, ISBN-1: 978-0138293697, 2024

AI & ML in Cybersecurity: Your go to guide to Artificial Intelligence & Machine learning in Cybersecurity, Ms. Malini Rao, ISBN-13: 978-2854456370

Note:

. The class is highly practical.

. All topics have an AI component included

. Every week there is an assignment homework in the style of a CTF competition

. Every week there are prizes for the one to first solve the CTF of the week

. There are bonus assignments for the winter break

Time-table for winter semester 2025/2026:

Time-table is not available yet

Time-table for summer semester 2025/2026:

Time-table is not available yet

The course is a part of the following study plans:

• prg.ai Master (compulsory course in the program)