Migration from Classical Cryptography to Post-Quantum Cryptography
Beschreibung
Systematic analysis of replacing classical cryptographic primitives with post-quantum schemes in a selected application domain, including performance and security implications.
Students are expected to propose a concrete use case and critically review existing literature and standardization efforts to identify the current state of the art.
Voraussetzungen
Good understanding of applied cryptography, software architecture basics, analytical thinking.
Kontakt
Please write an E-Mail to florian.griesser@tum.de
Betreuer:
Energy Analysis of Post-Quantum Cryptography
Beschreibung
Measurement and analysis of the energy consumption of post-quantum cryptographic implementations. Optional exploration of optimization strategies to reduce energy usage.
Example:
https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=11392724
Voraussetzungen
C programming, basic cryptography, interest in embedded systems and experimental evaluation.
Kontakt
Please write an E-Mail to florian.griesser@tum.de
Betreuer:
Performance Optimization of a Post-Quantum Signature Scheme
Beschreibung
Analysis and low-level optimization of a post-quantum digital signature implementation on an embedded device.
Focus on runtime, memory footprint, and practical trade-offs.
Algorithms
https://csrc.nist.gov/projects/pqc-dig-sig/round-2-additional-signatures
Examples:
https://eprint.iacr.org/2025/1928
https://eprint.iacr.org/2025/1261
Voraussetzungen
Strong C programming skills, basic cryptography, interest in performance engineering.
Kontakt
Please write an E-Mail to florian.griesser@tum.de
Betreuer:
Analyzing Weight Distributions (in BIKE) via Syndrome Information
Beschreibung
BIKE (Bit Flipping Key Encapsulation) is a post-quantum key exchange scheme based on quasi-cyclic moderate-density parity-check (QC-MDPC) codes. Security relies on the hardness of decoding random linear codes, where an attacker only knows the public matrix H, the syndrome s, and the exact weight of the error vector.
In this project the student will generate large datasets of BIKE ciphertexts and corresponding error vectors, and design experiments to analyze whether the weight (or distribution) of the error vector can be predicted directly from the syndrome and the parity-check matrix.
This includes:
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Implementing dataset generation with fixed public keys and varying error vectors
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Designing statistical or machine-learning based approaches to estimate error weights
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Evaluating how predictable the error structure is and whether such predictability could weaken BIKE’s assumed hardness
Voraussetzungen
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Good understanding of (code-based) cryptography basics
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Programming skills in Python or C.
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Interest in post-quantum cryptography and side-channel/security analysis.
Kontakt
florian.griesser@tum.de