*[Erläuterungen zu Abschnitt 3](../Anleitungen_Hilfen/3_Leistungen.md)*
**(!) Teilnahmevoraussetzungen (DE)**
keine
**(!) Teilnahmevoraussetzungen (EN)**
none
**(!) Prüfungsbedingungen (DE)**
Klausur oder mündliche Prüfung (100 %).
**(!) Prüfungsbedingungen (EN)**
Written exam or oral examination (100 %).
### 4. Informationen für das Modulhandbuch
*[Erläuterungen zu Abschnitt 4](../Anleitungen_Hilfen/4_Infos_Modulhandbuch.md)*
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Wir bitten Angaben in allen Punkten zu machen, da diese für die (Re-)Akkreditierung
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**(!) Empfohlene Voraussetzungen (DE)**
Basic knowledge in IT security, databases, and machine learning e.g., as taught in lectures such as "IT-Security", "Databases and Information Systems ", and "Elements of Machine Learning and Data Science".
**(!) Empfohlene Voraussetzungen (EN)**
Basic knowledge in IT security, databases, and machine learning e.g., as taught in lectures such as "IT-Security", "Databases and Information Systems ", and "Elements of Machine Learning and Data Science".
**(!) Lernziele (DE)**
...
**(!) Lernziele (EN)**
This course will provide students with an understanding of the unique challenges of securely operating on industrial data and provide them with the necessary conceptual tools to properly secure industrial data.
Knowledge: Students will be familiar with the security challenges of industrial data, specifically focusing on unique properties of industrial data compared to other settings. Students will know about the various approaches to secure industrial data, covering different aspects of securing industrial data across files, databases, and machine learning.
Skills: After taking this course, students will be able to select and apply suitable conceptual tools to realize comprehensive security of industrial data. Based on an assessment of the individual constraints in a given industrial scenario, students will be able to select those security measures that are best applicable and prioritize their deployment.
Competences: Students will be able to identify and pinpoint challenges of securing industrial data across different domains. They will further be able to identify where standard security approaches can be adapted to secure industrial data and where dedicated security approaches are required.
**(!) Inhalt (DE)**
This course provides an introduction into current security problems surrounding industrial data and state-of-the-art security solutions. After an introduction into industrial data, how it is stored and processes, as well as prevalent security issues surrounding industrial data, students will learn about approaches to secure industrial data across files, databases, and machine learning. Topics include encryption and integrity-protection of structured industrial data in files, database security in industrial contexts, as well as machine learning security for industrial data. Across all topics, a special emphasis will be put on the privacy-preserving processing of industrial data.
**(!) Inhalt (EN)**
This course provides an introduction into current security problems surrounding industrial data and state-of-the-art security solutions. After an introduction into industrial data, how it is stored and processes, as well as prevalent security issues surrounding industrial data, students will learn about approaches to secure industrial data across files, databases, and machine learning. Topics include encryption and integrity-protection of structured industrial data in files, database security in industrial contexts, as well as machine learning security for industrial data. Across all topics, a special emphasis will be put on the privacy-preserving processing of industrial data.
**(!) Literatur**
Lecture slides. Pointers to further relevant literature will be provided during the lecture.
### 5a. SPOen, in denen das Modul verankert werden soll
*[Erläuterungen zu Abschnitt 5a/5b](../Anleitungen_Hilfen/5_Studiengänge.md)*
