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AI and Security (CE-DAS)

AI and Security (CE-DAS)

Studiengänge
Masterstudiengang Wirtschaftsinformatik (MSc WI 19) (01.09.2019)
AI techniques play an increasingly important role for modern security mechanisms. They are crucial for timely detection of attacks, discovery and analysis of security vulnerabilities, analysis of malicious software. On the other hand, AI methods themselves can be victims of data manipulation and poisoning, or be used by attackers for malicious purposes. AI and Security provides on overview of selected applications of AI techniques in security and reveals the fundamental mechanisms required for assessment of security of AI. Specific topics covered by the course include but are not limited to the following:

  • AI methods for intrusion detection
  • Malware analysis by means of AI methods
  • AI methods for network security
  • Data manipulation attacks against AI methods
  • Security of AI in practical context
  • Offensive AI
Lernergebnisse
Learning Outcomes

After successful completion of the course, students will

Professional competence
  • understand main use cases for deploying AI in security context
  • understand security threats to AI systems
  • understand main use cases for AI abuse in security context

Methodological competence
  • use state-of-the-art intrusion detection technologies
  • understand the main design principles of AI driven security tools

Social competence
  • be able to organise learning materials and can solve problems independently
  • understand how certain security mechanisms can be broken
  • develop a “security mindset”

Personal competence
  • address new challenges and independent finding of viable solutions
  • think “out of the box” and can apply knowledge in unusual contexts

Technological competence
  • be familiar with intermediate-level security monitoring tools
Literatur
  • Students will be provided with relevant material (presentations, additional reading
Prüfungsmodalitäten
Written exam
Modulnummer:
6212039
Semester:
WS 26/27
ECTS-Credits:
3
Lehre:
28 L / 21 h
Selbststudium:
69 h
Plansemester:
3