Cybersecurity Data Science (VL) |
Untertitel: |
This course is part of the module: Cybersecurity Data Science |
Semester: |
SoSe 24 |
Veranstaltungstyp: |
Vorlesung (Lehre) |
Veranstaltungsnummer: |
lv2914_s24 |
DozentIn: |
Riccardo Scandariato, Ina Weigl, Dr. Nicolás Díaz Ferreyra, Catherine Tony, Torge Hinrichs, Emanuele Iannone |
Beschreibung: |
Theoretical Foundations: - Introduction to data science
- Supervised and unsupervised learning
- Data science methods (e.g., clustering, decision trees, artificial neural networks)
- Performance metrics
Cybersecutrity Applications: - Spam detection
- Phishing detection
- Intrusion detection
- Access-control prediction
- Denial of Service (DoS) prediction
- Vulnerability/malware prediction
- Adversarial machine learning
|
Leistungsnachweis: |
m1773-2022 - Cybersecurity Data Science<ul><li>p1760-2022 - Cybersecurity Data Science: Klausur schriftlich</li></ul><br>m1773-2023 - Cybersecurity Data Science<ul><li>p1760-2022 - Cybersecurity Data Science: Klausur schriftlich</li><li>vl440-2023 - Voluntary Course Work Cybersecurity Data Science - Subject theoretical and practical work: Subject theoretical and practical work</li></ul> |
ECTS-Kreditpunkte: |
3 |
Weitere Informationen aus Stud.IP zu dieser Veranstaltung |
Heimatinstitut: Institut für Software Security (E-22)
In Stud.IP angemeldete Teilnehmer: 144
Anzahl der Dokumente im Stud.IP-Downloadbereich: 13
|