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I regularly offer theses in the fields of probabilistic shaping, coding for high-throuput applications, and algorithms for communication. Please reach out if you are interested in a thesis in any of my research fields. A good background in information theory and channel coding are preferable, but the requirements generally depend on your interests.

Please include a description of your interests and corresponding academic background in your application. If you have a thesis idea, I am happy to discuss your suggestions. Also, I am available to supervise external theses as long as they are in my field of expertise.

Modern networked systems increasingly rely on intelligent information exchange between sensing devices and decision-making agents. Rather than sending data continuously or periodically, future communication networks aim to transmit only what matters: information that is useful, timely, and effective for achieving a specific goal.

Such goal-oriented communication is a key enabler of efficient cyber-physical systems, ranging from remote health monitoring and autonomous vehicles to industrial automation. Designing these systems requires new models that balance data freshness, communication cost, and decision accuracy.

This thesis will explore and model decision-making mechanisms for intelligent update systems where both sender and receiver actively decide when and what information to exchange. The goal is to investigate how coordinated or independent policies can improve overall system efficiency and effectiveness.

Possible directions include:

• Modeling joint decision processes between sensing and actuation agents.
• Analyzing when an agent should send (push) or request (pull) updates.
• Developing and simulating policies that account for usefulness, timeliness, and cost of communication.
• Comparing rule-based (model-based) and learning-based (reinforcement) approaches

Voraussetzungen

I may not always have prepared thesis topics available. Please feel free to reach out if you are interested in working on a thesis within any of my research areas.

See more information and apply directly here: Intern/Master Thesis Student - Topic/Area - Huawei Research Center Germany

Background

Homomorphic Encryption (HE) is a powerful cryptographic paradigm that allows computations to be performed directly on encrypted data, without ever needing to decrypt it first. The result of such a computation, once decrypted, is identical to what would have been obtained by performing the same operation on the plaintext. This makes HE particularly attractive for privacy-preserving applications in cloud computing, medical data analysis, and machine learning, where sensitive data must be processed by an untrusted third party.

The Noise Problem

Modern HE schemes — such as BGV, BFV, and CKKS — are built on the hardness of lattice problems, most notably Learning With Errors (LWE) and its ring variant (RLWE). The security of these schemes relies on the presence of noise in ciphertexts. However, homomorphic operations cause this noise to grow. Left unchecked, this noise growth quickly renders ciphertexts undecryptable, fundamentally limiting the depth and complexity of computations that can be performed. Noise management is therefore a central challenge in practical HE.

Internship Task

Several techniques have been developed to control or reduce noise growth in HE schemes, such as bootstrapping, modulus switching, flattening and rescaling.

In this internship, the student will try to develop a new noise management technique. The student will then compare this new technique to the existing ones, compare their computational costs and performance. The student will complement this with practical experiments using established HE libraries.

References

[1] Gentry, C. "Fully Homomorphic Encryption Using Ideal Lattices." Proceedings of the 41st Annual ACM Symposium on Theory of Computing (STOC), pp. 169–178, 2009.

[2] Brakerski, Z. and Vaikuntanathan, V. "Fully Homomorphic Encryption from Ring-LWE and Security for Key Dependent Messages." Advances in Cryptology – CRYPTO 2011, Lecture Notes in Computer Science, vol. 6841, Springer, 2011.

[3] Brakerski, Z., Gentry, C., and Vaikuntanathan, V. "(Leveled) Fully Homomorphic Encryption without Bootstrapping." Proceedings of the 3rd Innovations in Theoretical Computer Science Conference (ITCS), pp. 309–325, 2012.

[4] Fan, J. and Vercauteren, F. "Somewhat Practical Fully Homomorphic Encryption." Cryptology ePrint Archive, Report 2012/144, 2012.

[5] Cheon, J. H., Kim, A., Kim, M., and Song, Y. "Homomorphic Encryption for Arithmetic of Approximate Numbers." Advances in Cryptology – ASIACRYPT 2017, Lecture Notes in Computer Science, vol. 10624, Springer, pp. 409–437, 2017.

[6] Gentry, C., Sahai, A., and Waters, B. "Homomorphic Encryption from Learning with Errors: Conceptually Simpler, Asymptotically Faster, Attribute-Based." Advances in Cryptology – CRYPTO 2013, Lecture Notes in Computer Science, vol. 8042, Springer, pp. 75–92, 2013.

Post-quantum cryptography (PQC) has been an active area of research since the seminal work of Shor. 
Indeed, most public-key cryptography currently deployed (such as RSA and elliptic-curve-based schemes) is vulnerable to quantum adversaries. 
This applies in particular to public-key encryption (PKE) schemes.  
An attacker could record encrypted traffic and later decrypt it once a sufficiently capable quantum computer becomes available - a strategy known as "harvest now, decrypt later."

Post-quantum secure alternatives can be constructed from hard problems on codes and lattices. The recently standardized Kyber and HQC follow an encryption-based approach, while, e.g., NewHope is based on a key reconciliation mechanism:
Alice and Bob obtain noise variants of a common secret, and error correction removes this noise, allowing them to agree on the same shared key.

This project will survey constructions for exchanging a key in code-based and lattice-based cryptography. These constructions are to be categorized based on key properties, such as underlying metric, bandwidth requirements, and underlying assumptions.
First, an overview of the key techniques is to be developed.
Then, you are going to analyze whether they can be transferred from codes to lattices and vice versa. The project requires reading and understanding the literature on lattice- and code-based KEMs; a good starting point can be the following works:

Aguilar-Melchor, Carlos, et al. "Efficient encryption from random quasi-cyclic codes." IEEE Transactions on Information Theory 64.5 (2018): 3927-3943.

Bos, Joppe, et al. "CRYSTALS-Kyber: a CCA-secure module-lattice-based KEM." 2018 IEEE European symposium on security and privacy (EuroS&P). IEEE, 2018.

Alkim, Erdem, et al. "Post-quantum Key Exchange — A new hope." 25th USENIX security symposium (USENIX Security 16). 2016.

Voraussetzungen

I regularly offer theses in the fields of probabilistic shaping, coding for high-throuput applications, and algorithms for communication. Please reach out if you are interested in a thesis in any of my research fields. A good background in information theory and channel coding are preferable, but the requirements generally depend on your interests.

Please include a description of your interests and corresponding academic background in your application. If you have a thesis idea, I am happy to discuss your suggestions. Also, I am available to supervise external theses as long as they are in my field of expertise.

Wireless communication links used in control and automation systems must deliver timely and reliable information despite fading and packet losses. Hybrid Automatic Repeat reQuest (HARQ) protocols -combining forward error correction and retransmissions- can significantly improve reliability. However, retransmitting outdated packets can delay fresh information, leading to performance degradation in closed-loop systems.

This thesis aims to analyze and optimize HARQ scheduling for networked control from a communication-theoretic perspective. The project will study how retransmission strategies, feedback mechanisms, and channel dynamics jointly influence information freshness and system performance. The problem will be formulated within a stochastic decision framework, such as a Markov decision process (MDP), to characterize the trade-off between reliability, latency, and communication cost.

Possible research directions include:

Designing scheduling strategies that decide between new transmissions and retransmissions; 



The thesis combines ideas from communication theory, stochastic modeling, and decision-making under uncertainty, and provides an opportunity to contribute to ongoing research in low-latency and reliable communication for cyber-physical systems.

Voraussetzungen

Unsourced multi-access protocols ensure that multiple users can transmit on the same physical resources without pre-allocation of resources to the different users. To avoid information loss caused by collision of messages transmitted simultaneously, we investigate how to use (adaptive) coding schemes that allow the concurrent transmission of coded messages stemming from different users with lossless reconstruction of the payloads.

The student should be proficient in communications engineering and coding theory, i.e., the following prerequisites (or similar) are minimal requirements:

• Channel Coding
• Nachrichtentechnik

Federated learning allows to train a machine learning model in a distributed manner, i.e., the training data are collected and stored locally by users such as mobile devices or multiple institutes. The training is under the coordination of a central server and performed iteratively. In each iteration, the server sends the current global model to the users, who update their local model and send the local updates to the server for aggregation.

FL is proposed to protect user's sensitive data since these training data never leave the user devices. However, works have shown that the local updates still leaks information about the local datasets. To deal with this leakage, SecAgg[1] is proposed. Secure aggregation is to make sure that the server only obtains the aggregation of the local updates rather than each individual update.

However, recent work [2] has shown that, SecAgg only preserves privacy of the users in a single training round. Due to user selection in federated learning, by observing the aggregated models over multiple training rounds, the server is able to recoverindividual local models of the users.

The goal of this seminar is to study and understand SecAgg [1], the multi-round privacy leakage it suffers and how is this problem solved in [2]. 

[1]. Bonawitz, Keith, et al. "Practical secure aggregation for privacy-preserving machine learning." proceedings of the 2017 ACM SIGSAC Conference on Computer and Communications Security. 2017.

[2]. So, Jinhyun, et al. "Securing secure aggregation: Mitigating multi-round privacy leakage in federated learning." Proceedings of the AAAI Conference on Artificial Intelligence. Vol. 37. No. 8. 2023.

I may not always have prepared thesis topics available. Please feel free to reach out if you are interested in working on a thesis within any of my research areas.

Motivated by the cell-free and massive MIMO (multiple input multiple outputs) communication scenarios, the number of power amplifiers (PA), digital to analog converters (DAC), etc., is increased. Thus, using coarse quantized transmission reduces the channel's hardware cost and nonlinear effects. More details can be found here.

In this project, we investigate algorithms for mapping modulated data to coarsely quantized signals. We potentially employ linear or non-linear precoding techniques and receiver architectures, comparing our results with classical methods and neural networks.

The student needs an understanding of information theory and communication systems.

Background

Homomorphic Encryption (HE) is a powerful cryptographic paradigm that allows computations to be performed directly on encrypted data, without ever needing to decrypt it first. The result of such a computation, once decrypted, is identical to what would have been obtained by performing the same operation on the plaintext. This makes HE particularly attractive for privacy-preserving applications in cloud computing, medical data analysis, and machine learning, where sensitive data must be processed by an untrusted third party.

The Noise Problem

Modern HE schemes — such as BGV, BFV, and CKKS — are built on the hardness of lattice problems, most notably Learning With Errors (LWE) and its ring variant (RLWE). The security of these schemes relies on the presence of noise in ciphertexts. However, homomorphic operations cause this noise to grow. Left unchecked, this noise growth quickly renders ciphertexts undecryptable, fundamentally limiting the depth and complexity of computations that can be performed. Noise management is therefore a central challenge in practical HE.

Internship Task

Several techniques have been developed to control or reduce noise growth in HE schemes, such as bootstrapping, modulus switching, flattening and rescaling.

In this internship, the student will conduct a structured investigation of noise management techniques in homomorphic encryption. The goal is to develop a thorough and hands-on understanding of the state of the art. Concretely, the student will survey the techniques described above, study their theoretical underpinnings, compare their computational costs and noise behavior across different HE schemes (e.g., BGV, BFV, CKKS), and ideally complement this with practical experiments using an established HE library such as Microsoft SEAL or OpenFHE.

References

[1] Gentry, C. "Fully Homomorphic Encryption Using Ideal Lattices." Proceedings of the 41st Annual ACM Symposium on Theory of Computing (STOC), pp. 169–178, 2009.

[2] Brakerski, Z. and Vaikuntanathan, V. "Fully Homomorphic Encryption from Ring-LWE and Security for Key Dependent Messages." Advances in Cryptology – CRYPTO 2011, Lecture Notes in Computer Science, vol. 6841, Springer, 2011.

[3] Brakerski, Z., Gentry, C., and Vaikuntanathan, V. "(Leveled) Fully Homomorphic Encryption without Bootstrapping." Proceedings of the 3rd Innovations in Theoretical Computer Science Conference (ITCS), pp. 309–325, 2012.

[4] Fan, J. and Vercauteren, F. "Somewhat Practical Fully Homomorphic Encryption." Cryptology ePrint Archive, Report 2012/144, 2012.

[5] Cheon, J. H., Kim, A., Kim, M., and Song, Y. "Homomorphic Encryption for Arithmetic of Approximate Numbers." Advances in Cryptology – ASIACRYPT 2017, Lecture Notes in Computer Science, vol. 10624, Springer, pp. 409–437, 2017.

[6] Gentry, C., Sahai, A., and Waters, B. "Homomorphic Encryption from Learning with Errors: Conceptually Simpler, Asymptotically Faster, Attribute-Based." Advances in Cryptology – CRYPTO 2013, Lecture Notes in Computer Science, vol. 8042, Springer, pp. 75–92, 2013.

Machine-learning (ML) algorithms become increasingly popular tools for various ap-
plications. Since the hardware requirements to train ML algorithms is heavy, we of-
ten rely on service providers that provide pre-trained ML inference interfaces. To
ensure security of input data, we would like to send the our data in encrypted form
so that neither during transmission, nor the service provider can learn meaningful
information from the transmission and computations, but keeping up the function-
alities provided by ML algorithms.

Fully homomorphic encryption (FHE), an encryption scheme that allows various
computations on encrypted data, enables secure ML inference. Indeed, the user
who wishes to use a ML inference service can merely encrypt their data using an
FHE protocol. The service provider that knows, which FHE protocol has been used,
can run the encrypted version of the ML algorithm on the encrypted data and sends
back the encrypted response. Finally, the user decrypts and receives the inference
result.

In this project, we want to focus on one of the main parts of the ML inference steps,
namely, matrix-vector multiplication. Here, the matrix is a result of the training and
stored in plaintext on the server side. The vector is the user’s input data. During this
research internship, we assess the performance of different FHE protocols based on
lattices for the task of matrix-vector multiplication. Depending on the initial results,
we try to increase the efficiency using error correcting codes in lattice-based FHE
schemes, or to tailor the schemes to the present arithmetic task of matrix-vector
multiplication to increase the performance.

Secure Training for Machine-Learning
Note that this research internship only asks for a secure inference step. Training on
encrypted data, on the other hand, will not be feasible using FHE algorithms. In-
deed, while FHEs allow for general encrypted computations, the overhead increases
with the depth of the arithmetic circuits to be computed. The complexity of training
algorithms and the sheer amount of data required for training, makes encrypted
computations unrealistic in practice.

The MinRank and Rank Syndrome Decoding problem are the basis of the security of many cryptographic schemes. Therefore it is important to understand the complexity of solving these problems.

In this project, the goal is to:
1. Understand the the existing solvers for these problems, in particular, [1] and [2].
2. Apply some ideas to slightly improve their complexity.
3. Understand if it affects the security of the existing cryptographic schemes.

[1] Gaborit, Philippe, Olivier Ruatta, and Julien Schrek. 2016. “On the Complexity of the Rank Syndrome Decoding Problem.” IEEE Transactions on Information Theory 62 (2): 1006–19. https://doi.org/10.1109/TIT.2015.2511786.
[2] L. Goubin and N. T. Courtois, “Cryptanalysis of the TTM Cryptosystem,” in Advances in Cryptology — ASIACRYPT 2000, T. Okamoto, Ed., Berlin, Heidelberg: Springer, 2000, pp. 44–57. https://doi.org/10.1007/3-540-44448-3_4.

Voraussetzungen

Post-quantum cryptography (PQC) has been an active area of research since the seminal work of Shor. 
Indeed, most public-key cryptography currently deployed (such as RSA and elliptic-curve-based schemes) is vulnerable to quantum adversaries. 
This applies in particular to public-key encryption (PKE) schemes.  
An attacker could record encrypted traffic and later decrypt it once a sufficiently capable quantum computer becomes available - a strategy known as "harvest now, decrypt later."

Post-quantum secure alternatives can be constructed from hard problems on codes and lattices. The recently standardized Kyber and HQC follow an encryption-based approach, while, e.g., NewHope is based on a key reconciliation mechanism:
Alice and Bob obtain noise variants of a common secret, and error correction removes this noise, allowing them to agree on the same shared key.

This project will survey constructions for exchanging a key in code-based and lattice-based cryptography. These constructions are to be categorized based on key properties, such as underlying metric, bandwidth requirements, and underlying assumptions.
First, an overview of the key techniques is to be developed.
Then, you are going to analyze whether they can be transferred from codes to lattices and vice versa. The project requires reading and understanding the literature on lattice- and code-based KEMs; a good starting point can be the following works:

Aguilar-Melchor, Carlos, et al. "Efficient encryption from random quasi-cyclic codes." IEEE Transactions on Information Theory 64.5 (2018): 3927-3943.

Bos, Joppe, et al. "CRYSTALS-Kyber: a CCA-secure module-lattice-based KEM." 2018 IEEE European symposium on security and privacy (EuroS&P). IEEE, 2018.

Alkim, Erdem, et al. "Post-quantum Key Exchange — A new hope." 25th USENIX security symposium (USENIX Security 16). 2016.

Voraussetzungen

I regularly offer theses in the fields of probabilistic shaping, coding for high-throuput applications, and algorithms for communication. Please reach out if you are interested in a thesis in any of my research fields. A good background in information theory and channel coding are preferable, but the requirements generally depend on your interests.

Please include a description of your interests and corresponding academic background in your application. If you have a thesis idea, I am happy to discuss your suggestions. Also, I am available to supervise external theses as long as they are in my field of expertise.

I may not always have prepared thesis topics available. Please feel free to reach out if you are interested in working on a thesis within any of my research areas.

Motivated by the cell-free and massive MIMO (multiple input multiple outputs) communication scenarios, the number of power amplifiers (PA), digital to analog converters (DAC), etc., is increased. Thus, using coarse quantized transmission reduces the channel's hardware cost and nonlinear effects. More details can be found here.

In this project, we investigate algorithms for mapping modulated data to coarsely quantized signals. We potentially employ linear or non-linear precoding techniques and receiver architectures, comparing our results with classical methods and neural networks.

The student needs an understanding of information theory and communication systems.

I regularly offer theses in the fields of probabilistic shaping, coding for high-throuput applications, and algorithms for communication. Please reach out if you are interested in a thesis in any of my research fields. A good background in information theory and channel coding are preferable, but the requirements generally depend on your interests.

Please include a description of your interests and corresponding academic background in your application. If you have a thesis idea, I am happy to discuss your suggestions. Also, I am available to supervise external theses as long as they are in my field of expertise.

I may not always have prepared thesis topics available. Please feel free to reach out if you are interested in working on a thesis within any of my research areas.

Motivated by the cell-free and massive MIMO (multiple input multiple outputs) communication scenarios, the number of power amplifiers (PA), digital to analog converters (DAC), etc., is increased. Thus, using coarse quantized transmission reduces the channel's hardware cost and nonlinear effects. More details can be found here.

In this project, we investigate algorithms for mapping modulated data to coarsely quantized signals. We potentially employ linear or non-linear precoding techniques and receiver architectures, comparing our results with classical methods and neural networks.

The student needs an understanding of information theory and communication systems.