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

Dr.-Ing. Michael Pehl
Chair for Security in Information Technology
Head: Prof. Dr.-Ing. Georg Sigl
Technical University of Munich
Arcisstr. 21, 80333 Munich (Germany)

Email: m.pehl@tum.de

In side-channel analysis (SCA), an attacker exploits information leakage from power measurements, EM emanations and other sources to obtain the secret of the target device. PowerfulSCA attacks such as Template Attacks struggle under suboptimal conditions such as desyncronized traces and clock jitter in the DUT.

Recently, Deep Learning techniques have been proposed [1,2] to improve SCA. Furthermore, different data sets have been published [1,3] enabling the evaluation and comparison of different Deep Learning algorithms.

Depending on your background and type of work, possible tasks of this project include

• Develop a Convolutional Neural Network for SCA on existing datasets
• Compare Deep Learning Techniques to classical SCA (CPA, Template Attacks, ...)
• Create further datasets as base for machine learning evaluations.

This work can be conducted in English or German. In case of high quality of the work, results might be published.

References

[1] Prouff et al.: Study of Deep Learning Techniques for Side-Channel Analysis and Intro-duction to ASCAD Database, Cryptology ePrint Archive, Report 2018/053
[2] Cagli et al.: Convolutional Neural Networks with Data Augmentation Against Jitter-BasedCountermeasures, CHES 2017
[3] Riscure CHES 2018 CTF: https://chesctf.riscure.com/2018/content?show=training

• Basic understanding of machine learning algorithms (e.g. Neural Networks, ...)
• Basic understanding of side-channel analysis (e.g.  from visiting the lecture Sichere Implementierung kryptographischer Algorithmen and/or Smart Card Lab)
• Good programming skills in Python, ideally experience with Tensorflow and/or Pytorch

Technische Universität München
Lehrstuhl für Sicherheit in der Informationstechnik
Lars Tebelmann / Thomas Schamberger
Theresientr. 90, N1010
E-Mail: lars.tebelmann@tum.de / thomas.schamberger@tum.de

Cryptographic key storage is an important requirement in embedded devices. Physical Unclonable Functions(PUFs) provide a cost-efficient alternative to secure key storage. They exploit manifacturing variations to derive device-specific secrets for key storage and device authentication.

Side-channel analysis (SCA) of PUFs exploits the fact, that certain characteristics of the PUF structures and their surrounding evaluation circuitry can be observed by an attacker, e.g., by high-resolution localized EM measurements [1-3].

Depending on your background and type of work, possible tasks of this project include

• Get familiar with PUF primitives and their implementation
• Implement a PUF design (VHDL)
• Develop/Extend a measurement set-up for localized EM side-channel analysis (Python)
• Perform SCA on PUF primitives using the IC scanner positioning system in our lab

This work can be conducted in English or German. In case of high quality of the work, results might be published.

References
[1] Merli et al.: Semi-invasive EM Attack on FPGA RO PUFs and Countermeasures. 6th Workshop on Embedded Systems Security (WESS’2011), ACM, 2011
[2] Merli et al.: Localized electromagnetic analysis of RO PUFs. IEEE International Sympo-sium on Hardware-Oriented Security and Trust (HOST), 2013, 19-24
[3] Tebelmann et al.: Side-Channel Analysis of the TERO PUF. Constructive Side-Channel Analysis and Secure Design (COSADE), Springer International Publishing, 2019, 43-60

• Basic knowledge of lab equipment (e.g. oscilloscope, voltage suppply, ...)
• Good programming skills in Python
• Basic experience in the field of digital design (ideally VHDL/Vivado/Xilinx FPGAs)

Technische Universität München
Lehrstuhl für Sicherheit in der Informationstechnik
Lars Tebelmann
Theresientr. 90, N1010
E-Mail: lars.tebelmann@tum.de

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

Dr.-Ing. Michael Pehl
Chair for Security in Information Technology
Head: Prof. Dr.-Ing. Georg Sigl
Technical University of Munich
Arcisstr. 21, 80333 Munich (Germany)

Email: m.pehl@tum.de

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

Dr.-Ing. Michael Pehl
Chair for Security in Information Technology
Head: Prof. Dr.-Ing. Georg Sigl
Technical University of Munich
Arcisstr. 21, 80333 Munich (Germany)

Email: m.pehl@tum.de

In side-channel analysis (SCA), an attacker exploits information leakage from power measurements, EM emanations and other sources to obtain the secret of the target device. PowerfulSCA attacks such as Template Attacks struggle under suboptimal conditions such as desyncronized traces and clock jitter in the DUT.

Recently, Deep Learning techniques have been proposed [1,2] to improve SCA. Furthermore, different data sets have been published [1,3] enabling the evaluation and comparison of different Deep Learning algorithms.

Depending on your background and type of work, possible tasks of this project include

• Develop a Convolutional Neural Network for SCA on existing datasets
• Compare Deep Learning Techniques to classical SCA (CPA, Template Attacks, ...)
• Create further datasets as base for machine learning evaluations.

This work can be conducted in English or German. In case of high quality of the work, results might be published.

References

[1] Prouff et al.: Study of Deep Learning Techniques for Side-Channel Analysis and Intro-duction to ASCAD Database, Cryptology ePrint Archive, Report 2018/053
[2] Cagli et al.: Convolutional Neural Networks with Data Augmentation Against Jitter-BasedCountermeasures, CHES 2017
[3] Riscure CHES 2018 CTF: https://chesctf.riscure.com/2018/content?show=training

• Basic understanding of machine learning algorithms (e.g. Neural Networks, ...)
• Basic understanding of side-channel analysis (e.g.  from visiting the lecture Sichere Implementierung kryptographischer Algorithmen and/or Smart Card Lab)
• Good programming skills in Python, ideally experience with Tensorflow and/or Pytorch

Technische Universität München
Lehrstuhl für Sicherheit in der Informationstechnik
Lars Tebelmann / Thomas Schamberger
Theresientr. 90, N1010
E-Mail: lars.tebelmann@tum.de / thomas.schamberger@tum.de

Cryptographic key storage is an important requirement in embedded devices. Physical Unclonable Functions(PUFs) provide a cost-efficient alternative to secure key storage. They exploit manifacturing variations to derive device-specific secrets for key storage and device authentication.

Side-channel analysis (SCA) of PUFs exploits the fact, that certain characteristics of the PUF structures and their surrounding evaluation circuitry can be observed by an attacker, e.g., by high-resolution localized EM measurements [1-3].

Depending on your background and type of work, possible tasks of this project include

• Get familiar with PUF primitives and their implementation
• Implement a PUF design (VHDL)
• Develop/Extend a measurement set-up for localized EM side-channel analysis (Python)
• Perform SCA on PUF primitives using the IC scanner positioning system in our lab

This work can be conducted in English or German. In case of high quality of the work, results might be published.

References
[1] Merli et al.: Semi-invasive EM Attack on FPGA RO PUFs and Countermeasures. 6th Workshop on Embedded Systems Security (WESS’2011), ACM, 2011
[2] Merli et al.: Localized electromagnetic analysis of RO PUFs. IEEE International Sympo-sium on Hardware-Oriented Security and Trust (HOST), 2013, 19-24
[3] Tebelmann et al.: Side-Channel Analysis of the TERO PUF. Constructive Side-Channel Analysis and Secure Design (COSADE), Springer International Publishing, 2019, 43-60

• Basic knowledge of lab equipment (e.g. oscilloscope, voltage suppply, ...)
• Good programming skills in Python
• Basic experience in the field of digital design (ideally VHDL/Vivado/Xilinx FPGAs)

Technische Universität München
Lehrstuhl für Sicherheit in der Informationstechnik
Lars Tebelmann
Theresientr. 90, N1010
E-Mail: lars.tebelmann@tum.de

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

Dr.-Ing. Michael Pehl
Chair for Security in Information Technology
Head: Prof. Dr.-Ing. Georg Sigl
Technical University of Munich
Arcisstr. 21, 80333 Munich (Germany)

Email: m.pehl@tum.de

Die Vorlesung Sichere Implementierung kryptographischer Verfahren (SIKA) wird durch eine Übung begleitet, in der vier Programmieraufgaben durchgeführt werden. Zur Unterstützung der Studierenden, zur Betreuung des Seitenkanalmessplatzes und zum Testen der Abgabe-Umgebung wird ein/e Tutor/in gesucht.

Die Programmierübungen beinhalten die Implementierung von AES in C und die Entwicklung verschiedener Angriffe auf RSA und AES in Python. Im Rahmen des Differential Power Analysis(DPA)-Angriffs wird der Stromverbrauch einer Implementierung mit dem Oszilloskop aufgezeichnet. Für die Abgabe und Auswertung der Progammieraufgaben wird dabei die Coderunner-Umgebung aus Moodle verwendet.

Im Rahmen der Tätigkeit können für die Unterstützungbei den Progammieraufgaben feste Sprechzeiten am Lehrstuhl für Sicherheit in der Informationstechnik eingerichtet werden. Zum Testen von der Coderunner-Umgebung sollten die Aufgaben jeweils eine Woche vor dem Übungstermin eigenständig gelöst und abgegeben werden, um mögliche Probleme der Umgebung aufzudecken.

Zeitraum und Stundenanzahl:

Ab 15. Oktober 2020 bis 31. Januar 2021 mit 8-10 Stunden pro Woche, geringfügige Anpassung des Zeitraums und der Stundenzahl möglich.

• Programmierkenntnisse in C und Python
• Grundverständnis im Umgang mit Messgeräten, z.B. Oszilloskop
• Idealerweise Belegung der SIKA-Vorlesung in einem vorhergehenden Semester
• Eigenständige Arbeitsweise Semester

Technische Universität München
Lehrstuhl für Sicherheit in der Informationstechnik
Lars Tebelmann
Theresientr. 90, N1010
E-Mail: lars.tebelmann@tum.de