Master Praktikum: Cryptography

Rather than asking whether it is possible to break the code, one should ask whether it is feasible to break it.

Overview

The Master Praktikum in Cryptography explores the relationship between randomness and computation and is based on three interconnected domains, modern cryptography, probabilistic proofs, and pseudorandomness. Participants will gain a comprehensive understanding of foundational principles and methodologies of cryptography and have the opportunity to engage in the development of cryptographic projects, using the concepts discussed in the lecture.

Organization

• 2+2 hours per week

• Lecture: Lydia Kondylidou

• Tutorial: Tanguy Bozec

The course is divided into two parts. In the first part of the course, participants will receive an introduction on modern cryptography, probabilistic proof systems, and pseudorandom generators. Following this, the project phase will commence, with students working in teams of 3. Each team is tasked with delivering a presentation on relevant research articles, implementing a cryptographic project, and taking part in a code review process.

Evaluation will be based on the research, the functionality and security of the application, the effective use of cryptographic concepts and probabilistic proof systems, the robustness of pseudorandomness implementations, and the clarity of documentation.

Participation is limited to 30 master students.

Schedule

Tutorial: Monday 14:00 - 16:00 c.t. Oettingenstr. 67 - 061, Floor Plan

Lecture: Thursday 14:00 - 16:00 c.t. Oettingenstr. 67 - 061, Floor Plan

Chat

There is a Zulip chat room associated with the lecture where you can ask organizational and content-related questions. Please use it if possible, instead of sending us emails, so that your fellow students can also benefit from the answers.

Zulip-Stream: CryptoChat

Material

• Tutorials on the Foundations of Cryptography

• Modern Cryptography, Probabilistic Proofs and Pseudorandomness

• Pseudorandom Generators

Additional recommended reading

• N. Alon and J.H. Spencer: The Probabilistic Method. John Wiley Sons, Inc., 1992.
• O. Goldreich, Computational Complexity: A Conceptual Perspective, Cambridge University Press, 2008.
• R. Motwani and P. Raghavan: Randomized Algorithms. Cambridge University Press, 1995.
• R. Shaltiel: Recent Developments in Explicit Constructions of Extractors. In Current Trends in Theoretical Computer Science: The Challenge of the New Century, Vol 1: Algorithms and Complexity, World scietific, 2004. (Editors: G. Paun, G. Rozenberg and A. Salomaa.) Preliminary version in Bulletin of the EATCS 77, pages 67–95, 2002.