Seminar Topics

Oblivious transfer is a cryptographic protocol between a sender and a receiver. The server has multiple pieces of information, and according to which he/she has initially chosen, the receiver obtains only one of them. The sender remains oblivious to which information the receiver got.

Garbled circuits is the name of a cryptographic technique used for secure multi-party computation. It allows multiple parties to jointly compute a function on their private inputs, while preserving the privacy of the parties.

The task of the student is to understand the concept of garbled circuits ([4], [6]) based on oblivious transfer ([1], [2], [3], [5]).

References:

[1] W. Diffie and M. Hellman. New directions in cryptography. IEEE Transactions on Information Theory, 22(6):644–654, November 1976.

[2] Ronald L. Rivest, Adi Shamir, and Leonard M. Adleman. A method for obtaining digital signatures and public-key cryptosystems. Commun. ACM, 26:96–99, 1978.

[3] Michael Rabin. How to exchange secrets with oblivious transfer. 1981.

[4] Andrew C. Yao. Protocols for secure computations. In 23rd Annual Symposium on Foundations of Computer Science (sfcs 1982), pages 160–164, 1982.

[5] S. Even, O. Goldreich, and A. Lempel, “A randomized protocol for signing contracts,” Commun. ACM, vol. 28, pp. 637–647, 01 1985.

[6] Andrew Chi-Chih Yao. How to generate and exchange secrets. In 27th Annual Symposium on Foundations of Computer Science (sfcs 1986), pages 162–167, 198.

Prerequisites

Private Information Retrieval (PIR) is the problem of retrieving a desired data from a server/s while preventing the server from finding out the retrieved data. The scenario we consider has two additional constraints. Firstly, there is only a single server to retrieve the data from, and secondly, the retrievers should remain oblivious to the data they are not initially interested in.

The task of the student is to understand comparatively analyze the proposed approaches to this problem in [1] and [2].

References:

[1] E. Kushilevitz and R. Ostrovsky. Replication is not needed: single database, computationally-private information retrieval. In Proceedings of the 38th Annual Symposium on Foundations of Computer Science, FOCS ’97, page 364, USA, 1997. IEEE Computer Society

[2] Carlos AGUILAR MELCHOR and Philippe GABORIT. A lattice-based computationally-efficient
private information retrieval protocol. Cryptology ePrint Archive, Paper 2007/446, 2007.

Prerequisites

Many data-driven applications can be modeled as a communication between a data curator and a data analyst, which queries a database for particular population statistics. When the individual database entries are considered sensitive information, the data curator can undertake additional measures to ensure privacy of individual database entries.

Differential Privacy (DP) [1] has become a popular notion for data privacy, measuring the ability of a curious data analyst to discriminate between the value of different sensitive database entries. To use DP in practical systems, it is important to understand the fundamental guarantees of a system that claims to ensure DP.

While it is sometimes believed that DP guarantees hold unconditionally and even in the presence of arbitrary side information, it has been shown that it is not possible to provide privacy and utility without making assumptions about how the data are generated [2]. In particular, dependence (correlation) between different database entries can be exploited to break the alleged privacy guarantees [3].

In this seminar topic, the student will make himself familiar with the definition and formal guarantees of DP and study the issues and pitalls of DP, particularly with a focus on dependent data distributions. The student will summarize his results in the form of a scientific presentation and a scientific article, based on her own reading of scientific papers. These include but are not necessarily limited to the recommended references [1-3].

[1] C. Dwork and A. Roth, “The Algorithmic Foundations of Differential Privacy,” TCS, 2014.

[2] D. Kifer and A. Machanavajjhala, "No free lunch in data privacy," Proceedings of the 2011 ACM SIGMOD International Conference on Management of Data (SIGMOD '11).

[3] C. Liu, S. Chakraborty, and P. Mittal, “Dependence Makes You Vulnerable: Differential Privacy Under Dependent Tuples,” in Proceedings of the Network and Distributed System Security Symposium, 2016.

There are scenarios where we wish to enable public access to a program (a function) without giving away any information about how the function is implemented.
For general circuits, this notion called virtual black box obfuscation is known to be impossible.
However, a weaker notion called indistinguishability obfuscation (iO) can be achieved.
Here, the obfuscations of two similarly-size circuits realizing the same function should be computationally indistinguishable from each other and reveal no more than some canonical form of the underlying function.
In some sense this is even the strongest achievable form of function obfuscation.

As of today, iO is too inefficient for almost all practical applications.
However, recent research has shown it may be used to build most cryptographic constructions of interest (assuming the existence of a one-way function).
For some of these it is even the only currently known way.

The student's task is to survey the literature to understand the formal definition, properties and applications of indistinguishability obfuscation (iO). More specifically, the student should aim to explain a recent construction [1] achieving this notion and the underlying hardness assumptions.

[1] Brakerski, Z., Döttling, N., Garg, S., & Malavolta, G. (2020). Factoring and pairings are not necessary for io: Circular-secure lwe suffices. Cryptology ePrint Archive. https://eprint.iacr.org/2020/1024

Prerequisites

Rank-matric codes are codes that live in a vector space that is endowed with a different metric than the Hamming metric: in the rank-metric the distance between two codewords, represented as matrices over a smaller field, is defined as the rank of their difference.

The theory of rank-metric codes has interesting connections to many topics in discrete mathematics and promissing applications to code-based cryptography and network coding.

In this seminar work, the student will study properties and constructions of rank-metric codes and one or more applications. The goal is to understand and summarize parts of the following papers:

[1] H. Bartz, L. Holzbaur, H. Liu, S. Puchinger, J. Renner, A. Wachter-Zeh (2022). “Rank-Metric Codes and Their Applications”. arXiv: 2203.12384  https://arxiv.org/pdf/2203.12384.pdf 

[2] K. Marshall, (2016). “A study of cryptographic systems based on Rank metric codes”, Dissertation, University of Zurich  https://www.zora.uzh.ch/id/eprint/127105/1/Diss%20Kyle.pdf

[3] T. Randrianarisoa, (2018). “Rank metric codes, codes using linear complexity and applications to public key cryptosystems”, Dissertation, University of Zurich  https://www.zora.uzh.ch/id/eprint/153545/1/153545.pdf

[4] E. Gorla (2019). “Rank-metric codes”. arXiv: 1902.02650  https://arxiv.org/pdf/1902.02650.pdf

[5] E. Gorla and A. Ravagnani. (2018). “Codes endowed with the rank metric”. In: Network Coding and Subspace Designs. Springer. 3–23.  https://link.springer.com/content/pdf/10.1007/978-3-319-70293-3.pdf 

The "red alert problem" in information and coding theory refers to the challenges of error detection in communication systems, where a system may generate false positive alerts—indicating errors when none exist. This can lead to unnecessary retransmissions and resource waste. The critical challenge is to design robust error detection mechanisms that ensure reliable communication. In a scenario involving unequal error protection, a special message must maintain an extremely low probability of misdetection. In contrast, other messages must keep their average error probability under a certain threshold.   [1] B. Nazer, Y. Y. Shkel and S. C. Draper, "The AWGN Red Alert Problem," in IEEE Transactions on Information Theory, vol. 59, no. 4, pp. 2188-2200, April 2013, doi: 10.1109/TIT.2012.2235120 [2] B. Nazer and S. C. Draper, "Gaussian red alert exponents: Geometry and code constructions," 2010 48th Annual Allerton Conference on Communication, Control, and Computing (Allerton), Monticello, IL, USA, 2010, pp. 645-652, doi: 10.1109/ALLERTON.2010.5706968.   Interested students please contact: Alexander Sauter      alex.sauter@tum.de 

Prerequisites

Channel resolvability, introduced in [1] based on ideas from [2], measures how much needs to be transmitted to approximate a random variable at the channel output accurately.

Not only does it have deep ties to the capacity of a channel, but it is also an important tool in information theoretic secrecy, e.g., when communication should be hidden.

The goal of this topic is to understand and present the concept of resolvability, to outline it's relation to other channel properties such as capacity, and to illustrate its use in information theory by means of an exemplary application.

1. Han, Verdu. 1993. Approximation Theory of Output Statistics. https://doi.org/10.1109/18.256486
2. Wyner. 1975. The common information of two dependent random variables. https://doi.org/10.1109/TIT.1975.1055346

Prerequisites

In the last decade, cell-free massive MIMO [1] has emerged as one of the most promising technology for wireless communications. Many studies have been made to understand the advantages and the applications of these system design, especially recently for 6G communications [2]-[3]. There are many different possible applications for this technology, i.e. for Federated Learning [4], and different configurations has been investigated [5]. The goal of this seminar is to understand the concept of cell-free massive MIMO in wireless communiations and to give an overview explaining the pros and the cons, applying it also to communication scenarios.

[1] Nayebi, Elina, et al. "Cell-free massive MIMO systems." 2015 49th Asilomar Conference on Signals, Systems and Computers. IEEE, 2015.

[2] Elhoushy, Salah, Mohamed Ibrahim, and Walaa Hamouda. "Cell-free massive MIMO: A survey." IEEE Communications Surveys & Tutorials 24.1 (2021): 492-523.

[3] He, Hengtao, et al. "Cell-free massive MIMO for 6G wireless communication networks." Journal of Communications and Information Networks 6.4 (2021): 321-335.

[4] Vu, Tung Thanh, et al. "Cell-free massive MIMO for wireless federated learning." IEEE Transactions on Wireless Communications 19.10 (2020): 6377-6392.

[5] Björnson, Emil, and Luca Sanguinetti. "Scalable cell-free massive MIMO systems." IEEE Transactions on Communications 68.7 (2020): 4247-4261.

The estimation of a linearly transformed random vector from noisy measurements can be done efficiently by Approximate Message Passing (AMP). AMP is a computationally efficient algorithm that approximates max-sum and sum-product loopy belief propagation (BP). The generalization [1] extends AMP to allow arbitrary separable prior distributions and (non-linear) measurement channels.

The student should be able to understand and interpret the blocks of the generalized AMP. In addition, it should be understood that generalized AMP is a quadratic approximation of loopy BP for MAP estimation.

The literature research should include at least [1].

[1] S. Rangan, "Generalized approximate message passing for estimation with random linear mixing," 2011 IEEE International Symposium on Information Theory Proceedings, St. Petersburg, Russia, 2011, pp. 2168-2172, doi: 10.1109/ISIT.2011.6033942.

Prerequisites

For high-throughput communications, such as high-speed fiber optics or 8K video streaming, minimizing the complexity and power consumption of the decoding process is crucial. Soft-decision decoding (SDD), which provides state-of-the-art coding gains, is typically impractical in such scenarios due to its high complexity. In contrast, hard-decision decoding (HDD) is highly power-efficient but offers lower coding gains. Hybrid decoding aims to enhance HDD by incorporating soft information without significantly increasing complexity. The student's task is to review and compare some solutions from the literature concerning hybrid decoding of product-like codes.

• IBDD with scaled reliability/ combined reliability - https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=8832202 / https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9435057
• Soft-Aided bit marking - https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=8856224
• Anchor decoding - https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=8316914
• Dynamic reliability score decoder - https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9868117

Prerequisites

In cryptography, an oblivious transfer (OT) protocol is a type of protocol in which a sender transfers one of potentially many pieces of information to a receiver, but remains oblivious as to what piece (if any) has been transferred.   Often seen as an enemy, noise turned out to be a good ally of cryptographers. While a noiseless channel, from a cryptographic point of view, is a sterile medium where information theoretical security cannot be achieved for two parties, noise provides us with oblivious transfer (OT), the most powerful two-party primitive.   https://link.springer.com/chapter/10.1007/978-3-642-36899-8_6   https://ieeexplore.ieee.org/document/4529286   https://ieeexplore.ieee.org/document/8000673

Prerequisites

The students task is to understand and summarize the methods in [1], where biased codewords of a convolutional code were created. The methods are applied to LMMSE based channel estimation in [1], but could also be applied for probabilistic shaping [2]. The student should point out how this can be achieved.

[1] https://ieeexplore.ieee.org/abstract/document/6528082

[2] https://ieeexplore.ieee.org/document/8627924

Prerequisites

As there are continuously increasing throughput demands on fiber optical networks, many types of multiplexing systems have become a hot topic for research as there is a need to better utilize the bandwidth resources of the optical fiber and increase spectral efficiency, some of these allow of unique joint Digital Signal Processing. Carrier phase estimation is an important aspect of DSP-based receivers, through carrier phase estimation the effects of laser phase noise are mitigated, the effects of laser phase noise are in general more important as systems become more spectrally efficient. Traditionally carrier and phase recovery is done per channel basis using either blind or data aided methods, however some methods are able to exploit correlation between the channels and other such properties to perform joint carrier and phase recovery.

This topic focuses mainly on joint carrier and phase recovery algorithms and their performance. This topic looks at Frequency Comb-Based Transmission Systems and how in those systems the phase coherence between the lines can be exploited to simplify or increase the performance of digital carrier phase recovery algorithms and comparisons are made between different algorithms and different pilot distributions over the channels.

Papers:

1. Frequency Comb-Based WDM Transmission Systems Enabling Joint Signal Processing, Lars Lundberg et al

2. Joint Carrier Recovery for DSP Complexity Reduction in Frequency Comb-Based Superchannel Transceivers, Lars Lundberg et al

3. Pilot-Aided Joint-Channel Carrier-Phase Estimation in Space-Division Multiplexed Multicore Fiber Transmission, Arni F. Alfredsson et al                

4. Optimization of Pilot-Aided Joint Phase Recovery for Frequency Comb-Based Wideband Transmission, Gabriele Di Rosa et al

Interested student please contact Muhammad Ahmed Leghari for further discussion

Contact: ahmed.leghari@adtran.com

Optical communication systems are the backbone of current communication network as they allow fast and reliable information exchange. However, the advent of new generation applications and services require an ever increasing demand for higher capacity, lower cost, and lower energy consumption. According to discussions in [1], because of the difference in the growth rates between the fiber capacity and the traffic demand, there is expected to be a capacity shortage within the next decade. 

Among several options for increasing the capacity of installed optical fibers, exploiting new wavelength bands appears to be a promising and economical solution. Extending the transmission bandwidth from conventional band (C-band) to multi-band (MB), researchers are aiming to transmit information over the entire single mode fiber spectrum. This will increase the optical capacity and thus postpone the need to deploy new fibers. 

The challenges for the realization of such multiband networks lie both in the development of key components – as well as in the modelling of the physical and network layers. 

The modelling of UWB systems enables to optimize the design of a given optical communication link to achieve maximum throughput, including finding optimal signal launch power, data rates, modulation formats, number of channels, and, in the case of hybrid-amplified links, also the Raman amplifier’s pump powers and frequencies. The Gaussian noise closed-form model (GN-CFM) expressions [2] have increasingly been used for rapid evaluation of nonlinear interference (NLI) noise, which, together with amplified spontaneous emission (ASE) noise and transceiver noise, define the received SNR. GN-CFM, in turn, can be used to optimize optical link parameters.

The main paper of the seminar work [3] uses the GN model discussed in [4] [5] to calculate optimum launch power per channel with the presence of Raman amplification. The student’s task is to deliver the steps they used in paper [3] as well as to understand the mechanics of a hybrid amplification schemes and GN model defined in [4] [5].  

[1] Essiambre, René-Jean and Robert W. Tkach. “Capacity Trends and Limits of Optical Communication Networks.” Proceedings of the IEEE 100 (2012): 1035-1055.

[2] D. Semrau, R. I. Killey, and P. Bayvel, “A Closed-Form Approximation of the Gaussian Noise Model in the Presence of Inter-Channel Stimulated Raman Scattering,” Journal of Lightwave Technology, vol. 37, pp. 1924–1936, May 2019.

[3] H. Buglia, E. Sillekens, L. Galdino, R. I. Killey, and P. Bayvel, "Impact of launch power optimisation in hybrid-amplified links," 2024. 

[4]H. Buglia, E. Sillekens, L. Galdino, R. I. Killey, and P. Bayvel, “Throughput maximisation in ultra-wideband hybrid-amplified links”, in Optical Fiber Communications Conference, 2024, Tu3H.5.

[5]H. Buglia, M. Jarmolovicius, L. Galdino, R. I. Killey, ? and P. Bayvel, “A closed-form expression for the Gaussian noise model in the presence of Raman amplification”, Journal of Lightwave Technology, vol. 42, no. 2, pp. 636–648, 2024. DOI: 10.1109/JLT.2023.3315127.

the capacity of optical transmission system is limitted by the nonlinear effects in the fiber.

the digital back propagation(DBP) is a method to sovle this problem.

By reading some papers, student can get the principle of this method and its advantage.

it's better for student to have some basic knowledge about optical transmission system, nonlinear effects and digital signal processing.

Digital coherent optical receivers have revolutionized optical transmission system design through the integration of advanced subsystems and algorithms. This paper presents a comprehensive analysis of these components, including the optical front end, analog-to-digital converter (ADC), and digital signal processing (DSP) algorithms that contribute to the performance of the system. The paper delves into the methods used to compensate for transmission impairments, both static and dynamic, with a particular focus on dynamic-channel equalization.

[1] S. J. Savory, "Digital Coherent Optical Receivers: Algorithms and Subsystems," in IEEE Journal of Selected Topics in Quantum Electronics, vol. 16, no. 5, pp. 1164-1179, Sept.-Oct. 2010.

Prerequisites