Teaching at the Professorship of Cyber Trust

Course Instructor: Prof. Jens Grossklags, Ph.D.

Description:

Cybercriminal activities as well as other undesirable or malicious activities have increased in prevalence over the last decade. At the same time, the efforts and capabilities of industrial and academic researchers to understand these phenomena have made significant improvements. In this seminar, we will discuss a range of recent data-driven studies focusing, for example, on Spear-Phishing, Ransomware, Cybercriminal Marketplaces, Online Fraud etc., but also other challenges of societal interest such as Cyber-Bullying and Fake News. Each participant of the seminar will deeply engage with a key study to understand its focus, methodology, (data) limitations, and achievements. It is further expected to understand each work in the context of related studies, e.g., from security industry research labs. Participants of the seminar are expected to build on the literature to develop research objectives for further study, and/or top pursue their own studies within the scope of the seminar.

Requirement:

No specific knowledge required. General interest in interdisciplinary privacy and security topics highly desirable; knowledge in diverse methods of data analytics desirable for practical topics. The seminar language is English.

Note:

The seminar will meet for 1-2 introductory sessions at the beginning of the semester (there will be no pre-course meeting). The presentation of results will follow in the second half of the semester in the form of longer seminar sessions (Blocktermine). Students are expected to deliver a concise report and a comprehensive presentation about their findings. The exact timeline will be discussed in the introductory sessions. The formation of 2-person teams is possible with approval by the instructor.

According to the policy of our chair, deregistration from courses is possible until the first regular course meeting by written notice to the instructor. Further, regular attendance and participation in seminar meetings will be compulsory and also be part of the assessment.

TUM Online: Course description

Application via  http://docmatching.in.tum.de/

Course Instructor: Emmanuel Syrmoudis

Description:

The seminar explores the nascent and growing field of the economics of privacy and cyber security and related security/risk governance aspects. Personal information has become a primary economic good for legitimate companies and is collected for countless purposes. For example, targeted advertisements, personalization and price discrimination are enabled by the automated wholesale accumulation of users’ trails; online and offline. Given this background, the key objective of the seminar is a better understanding of the current and future marketplace for personal information. We will draw on methods from computer science as well as the economic and behavioral sciences to contribute to a rigorous comprehension of the challenges and solution approaches for current privacy and security challenges.

SPECIAL FOCUS TOPIC WINTER 2024: In this seminar, we will focus on an economic response to the growing abuse of (browser and device) fingerprinting techniques in the online advertisement space to complement the engineering-oriented view on the problem. Seminar theses will focus on assessing the state-of-the-art of fingerprinting techniques, on a conceptualization of monetization approaches in the context of fingerprinting, on evaluating the initiatives from large stakeholders (e.g., Apple, Google) to address fingerprinting, and other solution approaches.

Course objectives:

Seminar meetings will be held in the lecture period during the semester. The presentation of results will follow in the final weeks of the lecture period.

Meetings take place in Garching, online / hybrid participation is not possible.

Students are expected to deliver a concise report and a comprehensive presentation about their findings. The exact timeline will be discussed in the introductory sessions. Collaboration in two-person teams is possible with agreement of the instructor.

Requirement:
No specific knowledge required. General interest in interdisciplinary privacy and security topics highly desirable. The seminar language is English.

Note:

Information and materials will be made available via Moodle.

Regular seminar meeting is planned for Tuesday, between 10.00 and 12.30 in room 01.08.033 (CIT building Garching).

According to the policy of our chair, deregistration from courses is possible until the first regular course meeting by written notice to the instructor. Further, regular attendance and participation in seminar meetings will be compulsory and also be part of the assessment.

Application via http://docmatching.in.tum.de/

TUM Online: Course Description

Pre-course meeting:
We will hold an information meeting on 03.07.24, 11:00 - 11:30 via Zoom:
https://tum-conf.zoom-x.de/j/61660272433?pwd=PEDffCBIWdr61Yc3aixKVCRZ5tjm33.1
Meeting ID: 616 6027 2433
Passcode: 508601

Course Instructor: Mo Chen, Ph.D.

Description:

Behavioral insights are “an inductive approach to policy-making combining fundamental insights from psychology, cognitive science, and social science with empirically-tested results to discover how humans actually make choices” (by OECD). There is a trend of governments and organizations applying behavioral insights to public policy to shape and influence behavior. At the same time, the past decade witnessed a global interest in digital tools to influence behavior. Tools driven by the rapidly advancing technology development around big data as well as artificial intelligence (AI) are increasingly integrated in social governance. As a result, behavioral insights can now function as a policy-making tool to utilize the insights generated by big data, and the relationship between behavioral insights and big data is growing ever closer. In the seminar, we will deepen our understanding of behavioral insights in public policy making from an interdisciplinary point of view.

Course objectives:

Understand behavioral insights in public policy making from an interdisciplinary point of view.
Become familiar with the basic concepts and application of nudging in public policy.

Prepare and write a scientific paper (English; 8-10 pages)
Conduct a presentation of your topic (English; 15 minutes + 10 minutes discussion)

Requirement:
Strong interest in interdisciplinary work.

Note:
Regular seminar meeting is planned for Tuesday, between 12.00 and 14.00 in room 00.13.054 (CIT building Garching).

According to the policy of our chair, deregistration from courses is possible until the first regular course meeting by written notice to the instructor. Further, regular attendance and participation in seminar meetings will be compulsory and also be part of the assessment.

TUM Online: Course Description

Application via http://docmatching.in.tum.de/

Course Instructor: Chiara Ullstein

Description:

The seminar aims to familiarise students with the EU AI Act (artificial intelligence regulation) and explore how participatory AI can help operationalize selected provisions of the EU AI Act. By working with the AI Act, students learn to read a legal text, understand what it means for AI to be in compliance with specific provisions of the AI Act, and familiarize themselves with approaches to participatory AI. Participatory AI can play a critical role in operationalizing AI regulation by fostering an inclusive framework that draws on diverse stakeholders' collective expertise, values, and perspectives. This approach can be perceived as valuable because AI technologies are not developed or deployed in a vacuum; they affect a broad spectrum of social, economic, and ethical realms. By involving a wide range of participants, including technologists, policymakers, ethicists, business leaders, civil society, laypeople, and others, Participatory AI may help ensure that AI development and AI governance are well-informed and reflect societal values. The exploration of approaches to Participatory AI to meet selected Articles of the EU AI Act is the focus of this seminar. The seminar is divided into two phases: 1) In the first phase, the EU AI Act and Participatory AI will be introduced. Students will learn to understand the structure of the proposal and how to interpret it. As part of the introduction to the AI Act, participants will also learn about the context of the EU AI Act, the legislative processes of the European Union, and where the draft AI Act is currently at. Participants will present either provisions of the AI Act or a paper on Participatory AI. The presentations serve to develop a foundational understanding of the EU AI Act and Participatory AI. 2) In the second phase, student teams select one article from the EU AI Act and develop a strategy or suggestions on how participatory AI could be a means to ensure or contribute to legal compliance with the article. Teams will first present a proposal in the seminar. Then, student teams develop their work in the form of a seminar paper after receiving feedback. At the end of the seminar, they will give a presentation of their work and hand in a seminar paper. The goal of the seminar is to make students familiar with AI regulation developed by the EU and to sensitize them for approaches to Participatory AI. For the teamwork, the goal is to bring together students from the Informatics & Mathematics Department and the Governance Department to foster interdisciplinary discussion.

Course objectives:

Understand what the AI Act is about and how it influences the development of AI systems. Become familiar with the analysis, critical reading, and application of legislative text.
Understand what Participatory AI is and how it can be beneficially applied to realize provisions of the EU AI Act.

Deliverables:
- Presentation (English; 10 min presentation per person+ 5 min discussion)
- Written Seminar Paper (English; ~3000 words per student in teams of two people)

Requirement:
Interest in AI regulation and/or experience with the development of AI; Interest in approaches to Participatory AI

IMPORTANT:

Application: Please apply by October 6 via email to chiara.ullstein@tum.de (subject line: [AI Act Seminar] – application; please indicate (1) your full name, (2) study subject, (3) Bachelor/Master, (4) year in the specified program, (5) matriculation number, (6) 1-2 sentences concerning your motovation to participate). Seminar places will be confirmed October 7.

Participation is reserved for students from the Governance Department (50%) and Informatics & Mathematics Department (50%).

Information and materials will be made available via Moodle

Kick-off Meeting: In the week of October 7 (before the first week of lecture period)

- Date: October 9

- Location (meeting room): tba

Planned course timeline:

09.10. Introduction to the AI Act and Participatory AI (14:00 – 18:00; Room: Arcisstr. 21 1229, Seminarraum (0502.01.229))
10.10. Exploration of the AI Act and approaches to participation (14:00 – 18:00; Room: Arcisstr. 21 1229, Seminarraum (0502.01.229))
18.10. Student presentations on the AI Act/ Participatory AI (9:30 – 18:00; Room: will be announced soon)
19.10. Student presentations on the AI Act/ Participatory AI & Student’s proposal of seminar thesis topic (9:30 – 18:00; Room: Arcisstr.21 Z538, Building 0505)
Tba.11. mandatory feedback session
15.12. Submission of seminar thesis

Note: According to the policy of our chair, deregistration from courses is possible until the first regular course meeting by written notice to the instructor. Further, regular attendance and participation in seminar meetings will be compulsory and also be part of the assessment.

TUM Online: Course Description

Weekly group meeting of the Chair of Cyber Trust for members and guests of the chair. The seminar includes research discussions and talks about topics related to the activities of the chair.