Course Contents
This course provides a sound and practice-oriented introduction and an overview of the foundations, methods, and applications of human-computer-interaction (HCI) in the context of usable safety, security, and privacy. The course content is deepened in the application areas of cybersecurity, data protection, and crisis informatics. Methodologically, the spectrum from usability engineering to user experience design is covered from analysis through design to evaluation.
CONTENT:
[list]
[*]Foundations and Methods (Usability Engineering and User Experience Design)
[*]Usable Safety (Crisis Informatics), Security (Cybersecurity) und Privacy (Data Protection)
[*]International/cultural aspects and trends
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STRUCTURE:
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[*]Introduction and Overview
[*]Foundations and Methods (Usability Engineering and User Experience Design of Safety- and Security-Critical Systems)
[*]Usable Safety (Business Continuity and Cooperation in Authorities, Public Warning in Disaster Events, Social Media in Emergencies, Crises and Catastrophes, Social Media Analytics for Companies and Authorities)
[*]Usable Security (Human Factors in Security, Tools for Usable (Cyber-)Security)
[*]Usable Privacy (Usable Solutions for Data Protection, Privacy-Enhancing Technologies)
[*]Outlook (International/ cultural aspects, Trends and Developments)
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Literature
Reuter, C. (Ed.) (2021) Sicherheitskritische Mensch-Computer-Interaktion: Interaktive Technologien und Soziale Medien im Krisen- und Sicherheitsmanagement, Wiesbaden: Springer Vieweg. [url]http://www.buch-sec-mci.chreu.de[/url]
Preconditions
Recommended prerequisites include a foundation in at least one of the following areas: computer science, cyber security and privacy, human-computer interaction, or peace and conflict studies, as well as basic knowledge of the subject areas covered by PEASEC.
Further Information
Further information on lectures of PEASEC can be found at [url=http://www.peasec.de/teaching]www.peasec.de/teaching[/url]
You can find the Moodle-course at [url=http://www.usp.peasec.de]www.usp.peasec.de[/url]
Online Offerings
moodle
- Lecturer: Kilian Demuth
- Lecturer: Markus Henkel
- Lecturer: Marc-André Kaufhold
- Lecturer: Christian Reuter
Course Contents
- Goals and challenges of explainability for computer vision
- Interpretability of classical machine learning models
- Global vs. local explanations
- Post hoc explanations
- Intrinsically explainable neural networks
- Evaluation of explanations
- Visualization techniques
- Applications of explanations
- XAI beyond classification
Preconditions
Basic knowledge of computer vision, machine learning, and deep learning. For example, acquired through the courses Computer Vision I, Introduction to Artificial Intelligence, Deep Learning: Architectures & Methods, and/or Statistical Machine Learning.
Online Offerings
moodle
- Lecturer: Simone Schaub-Meyer
Digital Teaching
Course website: https://encrypto.de/CRYPROT
Course Contents
Cryptographic protocols allow parties with potentially conflicting interests to jointly perform certain tasks. This course covers basic and advanced constructions for cryptographic protocols and their applications, including Commitments, Secure Coin Flipping, Zero-Knowledge Proofs, Mixnets, Anonymous Credentials, Private Information Retrieval, Secure Multiparty Computation, and Hardware-assisted Cryptographic Protocols.
Preconditions
Basic knowledge in applied cryptography is strongly recommended, e.g., by successfully completing the course "Computer System Security" or "Introduction to Cryptography".
Online Offerings
moodle
- Lecturer: Thomas Schneider
Course Contents
In this seminar the students will analyze and discuss the current state of the art on using (game) technology, methods and concepts for serious games (e.g. in education, health and sports).
At the beginning of the term we will introduce the specific topics, which can be chosen by one student each. During the term we will organize a review session where students give each other feedback on the current state of their report. There will be also regular meetings with your tutor. At the end of the term the results will be presented to the whole group in a single session for all participants (~ 10 minutes talk + 5 minutes questions); additionally a written report (approximately 20 pages) must be submitted.
The topics relate to current research questions in the field, partly in cooperation with partners from the games industry and/or Serious Games users, and are associated to the following areas:
[list]
[*]Digital Storytelling, Adventure Games and Story-based Edutainment Applications
[*]Authoring and Creation of (Multiplayer) Serious Games
[*]Game Mastering and Collaborative Gaming
[*]Social Serious Games
[*]User Generated Content
[*]Exergames, Games for Health and Sensors
[*]Mobile Gaming, Location-based Gaming and Urban Health Games
[*]Evaluation and Measurement of Effects
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Literature
Will be announced per topic.
Preconditions
It is recommended that students have completed or are currently enrolled in the Introduction to scientific work course
Expected Number of Participants
Max. 30
Online Offerings
Moodle Course: https://moodle.informatik.tu-darmstadt.de/course/view.php?id=1405
- Lecturer: Stefan Peter Göbel
Course Contents
- Statistical Methods for Machine Learning
- Refreshers on Statistics, Optimization and Linear Algebra
- Bayes Decision Theory
- Probability Density Estimation
- Non-Parametric Models
- Mixture Models and EM-Algorithms
- Linear Models for Classification and Regression
- Statistical Learning Theory
- Kernel Methods for Classification and Regression
Literature
1. C.M. Bishop, Pattern Recognition and Machine Learning (2006), Springer
2. K.P. Murphy, Machine Learning: a Probabilistic Perspective (expected 2012), MIT Press
3. D. Barber, Bayesian Reasoning and Machine Learning (2012), Cambridge University Press
4. T. Hastie, R. Tibshirani, and J. Friedman (2003), The Elements of Statistical Learning, Springer Verlag
5. D. MacKay, Information Theory, Inference, and Learning Algorithms (2003), Cambridge University Press
6. R.O. Duda, P.E. Hart, and D.G. Stork, Pattern Classification (2nd ed. 2001), Willey-Interscience
7. T.M. Mitchell, Machine Learning (1997), McGraw-Hill
- Lecturer: Marcus Rohrbach
- Lecturer: Simone Schaub-Meyer
In the event of a cyber incident like a Distributed Denial of Service (DDoS) attack, widespread malware infection, or data breach, organisations must act swiftly to continue or restore operations and maintain stakeholders' trust. This course delves into the concepts of decision-making in preparation and response to cyber incidents.
The focus in this course will be rational decision-making. Rational here means that the investments made and the measures taken should be both effective and efficient. As we will discuss quite some regularly taken measures aimed to improve cyber security have no proven proportionality.
We will use the concept of the safety chain to help determine what investments in preparation are effective and efficient.
Another core concept is the use of resilience in organizations. We discuss three interrelated concepts: a resilient cyber decision-making process, a resilient cyber decision, and a cyber resilient performance. As we will show the relationship between three concepts is not trivial. Drawing on the principles of naturalistic decision-making (NDM), we demonstrate that a resilient cyber decision-making process during cyber incidents requires anticipation of and overcoming inherent flaws in decision-making, which, while theoretically feasible, proves challenging for professionals under severe time constraints and uncertainty.
The course will furthermore rely on interaction of the students with their host-organization, for which the students will write an advice on proportional cyber security policies (see ‘examinierung’), so the students get an insight on practical cyber security.
Expected Number of Participants
max. 40
Further Information
[url]https://cipr.peasec.de[/url]
Additional Information
There will physical and online colleges, as well as an advice to be written.
The course will start with a two-day intensive and immersive session during which the basics of the governance of safety and security are covered. This will be the base for the specific course content on cyber incident preparation and response.
During the semester there will be weekly on-line colleges during which specific themes are covered, and the exam-advice development (see below under ‘Examinierung’) will be discussed.
Guest lectures will be given by o.a. dr. Jelle Groenendaal, o.a. former senior IT-security advisor with an international operating Dutch-based bank whose work will be part of the literature studied. This will give students the chance to interact with ‘reflective practitioners’ on the domain.
The course will end as it begins, that is with a two-day session in which the concept of the exam advice will be presented (this will be a base for the grades), discussed and whenever necessary improved.
Students must be present during the two-day sessions and during 90% of the online lectures as there will be no recordings due to the sometimes confidential content shared.
- Lecturer: Ira Helsloot
- Lecturer: Christian Reuter