PV302 AI and Cybersecurity

Fakulta informatiky
jaro 2027
Rozsah
2/1/0. 3 kr. (plus ukončení). Ukončení: zk.
Vyučováno kontaktně
Vyučující
RNDr. Valdemar Švábenský, Ph.D. (přednášející)
Garance
RNDr. Valdemar Švábenský, Ph.D.
Katedra počítačových systémů a komunikací – Fakulta informatiky
Dodavatelské pracoviště: Katedra počítačových systémů a komunikací – Fakulta informatiky
Předpoklady
SOUHLAS && PB177 Kyberútoky && ( PB015 AI: the Practical Perspective || NOW( PB015 AI: the Practical Perspective ) )
It is assumed that students already know standard cyber attack techniques, as well as the terminology and foundations of AI. Be sure to also read the full course catalog page.
If applying for an enrollment exception, briefly list your relevant experience and completed courses in the areas above, as well as your motivation for studying this course.
Omezení zápisu do předmětu
Předmět je otevřen studentům libovolného oboru.
Předmět si smí zapsat nejvýše 36 stud.
Momentální stav registrace a zápisu: zapsáno: 0/36, pouze zareg.: 0/36, pouze zareg. s předností (mateřské obory): 0/36
Anotace
This course focuses on domain-specific, targeted applications of AI in cybersecurity contexts. It aligns with the CyberAI Project supported by the US National Science Foundation (NSF) and the National Security Agency (NSA). This effort aims to train experts in cyber AI to meet the rapidly evolving requirements for working in the cybersecurity field.
Výstupy z učení
Upon completing the course, students will be able to:
  • Understand the relevance of AI-based methods and tools for cybersecurity applications.
  • Understand how attackers can misuse AI tools to conduct specialized cyber attacks.
  • Apply LLMs and other AI tools to detect and respond to cyber threats.
  • Critically evaluate the usefulness, effectiveness, and trustworthiness of AI-generated outputs within cybersecurity contexts.
  • Identify cybersecurity risks and associated threats in AI-driven systems.
  • Apply/Implement defensive countermeasures to prevent cyber attacks on AI-based systems.
Klíčová témata
The course covers knowledge, skills, and competencies in two complementary aspects:
a) SecureAI – Securing AI systems and infrastructure.
b) AICyber – Using AI for cybersecurity, i.e., in applications that support and enhance cybersecurity.
Specifically, the course covers:
  1. Case Studies of AI in Cybersecurity, the ATLAS framework
  2. Prompting Techniques to Enhance Cybersecurity Education
  3. Phishing & Social Engineering with LLMs
  4. OWASP Top 10 for LLM Applications
  5. AI-Powered Red Team Tools
  6. Cybersecurity-specific AI Models
  7. AI Tools for Supporting Cybersecurity Teams
  8. Adversarial Machine Learning & Attacks on AI Systems
  9. Deepfakes and AI-Driven Cybersecurity Threats

Studijní zdroje a literatura
  • MITRE ATLAS™: https://atlas.mitre.org/
  • OWASP GenAI Security Project: https://genai.owasp.org/
Přístupy, postupy a metody používané ve výuce
  • Lecture, which includes case studies, demonstrations, discussions, and interactive activities.
  • Practical exercises on a computer involving the hands-on usage of relevant tools in Linux.
  • Practical homework assignments involving the deployment of tools and experimentation.
Způsob ověření výstupů z učení a požadavky na ukončení

Students gain points towards the grade via the following:

  • Mini-test at the start of each seminar (6 tests total, in each of the 6 seminars), testing the content of the previous lecture(s) — 12% of the grade (2% for each test).
  • Two practical homework assignments, requiring the deployment of tools and writing an experience report with screenshots — 20% of the grade (10% for each homework).
  • Midterm exam — 20% of the grade.
  • Final exam — 40% of the grade.
  • Detailed, constructive feedback after each lecture and seminar, in order to help shape the course in future years — 8% of the grade (0.5% for each lecture or seminar, up to the maximum of 8%).

After achieving at least the passing grade (60% or more) on the criteria above, students can choose to improve their grade by completing an optional homework assignment. This involves creating a practical educational material relevant to the course topic. Up to 10% bonus points can be earned based on the quality of the output.

The grade is then determined based on this scale:

A 92 – 100%
B 84 – 91%
C 76 – 83%
D 68 – 75%
E 60 – 67%
F less than 60%
Vyučovací jazyk
Angličtina
Navazující předměty
Odkaz a informace vyučujících
From the student’s perspective, there are 2 hours of lecture per week, followed by a 2-hour exercise session bi-weekly (i.e., the seminar groups alternate every other week).

All study materials, tools, and literature are in English. The default spoken language of instruction is English for all lectures and seminars. If all attendees of a particular seminar group speak Czech or Slovak, the group may agree to switch to either language.

Další komentáře
Předmět je vyučován každoročně.
Výuka probíhá každý týden.
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