A Physical Unclonable Function (PUF) is a hardware element which uses subtle manufacturing variabilities to derive a device-unique secret. In the case of a multi-challenge PUF (or ‘strong PUF’), the PUF functions as a device-unqiue function, mapping challenges to PUF responses.

A PUF like this is very useful for authentication scenarios, where e.g. a server provides challenges to a device, which replies with the PUF response the server can now check against an internal model or response database.

Protocols like these, however, suffer from data leaks, allowing an attacker to create a model of a device’s PUF from captured challenge-response pairs. Thjus, the ostensibly unclonable device may be replicated just be eavesdropping on authentication communication.

The aim of this work is to investigate novel approaches for PUF authentication procedures which plug data leaks with simple on-device preprocessing while still allowing for reliable authentication in the presence of measurement noise. A software implementation can then be evaluated e.g. against a more standard implementation in terms of performance, complexity or resistance against a machine learning attack.

This work can either be conducted in German or in English.

I am happy to provide more details and answer your questions upon request.

• Necessary: Basic cryptography knowledge; mathematical background; programming skills
• Favourably: Experience with machine learning techniques
• Optionally: Basic knowledge of error-correcting codes, PUFs

Physical Unclonable Functions (PUFs) exploit manufacturing process variations to generate unique signatures. PUF and error-correcting codes can be joined together to reliably generate cryptographically strong keys. However, the implementation of error-correcting codes is prone to physical attacks like side-channel attacks. Side-channel attacks exploit the information leaked during the computation of secret intermediate states to recover the secret key. Therefore, the implementation of error-correcting codes must also involve the implementation of proper countermeasures against side-channel attacks.

The goal of this thesis is to evaluate the side-channel resistance of a secure implementation of error-correcting codes for PUFs on FPGA. The thesis consists of the following steps:

• Get familiar with currently available implementations of error-correcting codes for PUFs
• Adapt and improve current implementations (VHDL)
• Develop a measurement setup for side-channel analysis (Matlab/Python)
• Perform side-channel analysis using the state-of-the-art EMF measurement equipment in our lab (Oscilloscope knowledge + Matlab/Python required)

 The ideal candidate should have:

• Previous experience in field of digital design (VHDL/Vivado/Xilinx FPGA)
• Basic knowledge on using lab equipment (e.g Oscilloscope,...)
• Basic knowledge in statistics
• Good programming skills in Matlab/Python
• Attendance at the lecture “Secure Implementation of Cryptographic Algorithms” is advantageous

Silicon based Physical Unclonable Functions (PUFs) are security primitives which can be used to derive device unique identities. Such identities can be used to identify a device or to derive a secret key.

You are interested in research in the field of Physical Unclonable Functions but you think that the topics which are listed on our page do not fit your previous knowledge or think there is no perfect match to what you are interested in? No problem! Please contact me at any time for advice regarding your thesis/student job. I can offer to

• help you with your decision for/against some topic.
• suggest probably further topics which are not advertised, yet.
• bring you into contact with other members of our chair or at Fraunhofer AISEC.

Plese send me an email which exhaustively describes your previous knowledge (e.g. your last grading sheet and a short CV) to allow me to prepare and to give you reasonable advice. Also, please provide 3-5 dates, which fit to your schedule, for a meeting.