Codes on Graphs and More

Modern communication systems strive to achieve reliable and efficient information transmission and storage with affordable complexity. Hence, efficient low-complexity channel codes providing low probabilities for erroneous receptions are needed. Interpreting codes as graphs and graphs as codes opens new perspectives for constructing such channel codes. Low-density parity-check (LDPC) codes are one of the most recent examples of codes defined on graphs, providing a better bit error probability than other block codes, given the same decoding complexity. After an introduction to coding theory, different graphical representations for channel codes are reviewed. Based on ideas from graph theory, new algorithms are introduced to iteratively search for LDPC block codes with large girth and to determine their minimum distance. In particular, new LDPC block codes of different rates and with girth up to 24 are presented. Woven convolutional codes are introduced as a generalization of graph-based codes and an asymptotic bound on their free distance, namely, the Costello lower bound, is proven. Moreover, promising examples of woven convolutional codes are given, including a rate 5/20 code with overall constraint length 67 and free distance 120. The remaining part of this dissertation focuses on basic properties of convolutional codes. First, a recurrent equation to determine a closed form expression of the exact decoding bit error probability for convolutional codes is presented. The obtained closed form expression is evaluated for various realizations of encoders, including rate 1/2 and 2/3 encoders, of as many as 16 states. Moreover, MacWilliams-type identities are revisited and a recursion for sequences of spectra of truncated as well as tailbitten convolutional codes and their duals is derived. Finally, the dissertation is concluded with exhaustive searches for convolutional codes of various rates with either optimum free distance or optimum distance profile, extending previously published results

Analysis and Decoding of Linear Lee-Metric Codes with Application to Code-Based Cryptography

Lee-metric codes are defined over integer residue rings endowed with the Lee metric. Even though the metric is one of the oldest metric considered in coding-theroy and has interesting applications in, for instance, DNA storage and code-based cryptography, it received relatively few attentions compared to other distances like the Hamming metric or the rank metric. Hence, codes in the Lee metric are still less studied than codes in other metrics. Recently, the interest in the Lee metric increased due to its similarities with the Euclidean norm used in lattice-based cryptosystem. Additionally, it is a promising metric to reduce the key sizes or signature sizes in code-based cryptosystem. However, basic coding-theoretic concepts, such as a tight Singleton-like bound or the construction of optimal codes, are still open problems. Thus, in this thesis we focus on some open problems in the Lee metric and Lee-metric codes. Firstly, we introduce generalized weights for the Lee metric in different settings by adapting the existing theory for the Hamming metric over finite rings. We discuss their utility and derive new Singleton-like bounds in the Lee metric. Eventually, we abandon the classical idea of generalized weights and introduce generalized distances based on the algebraic structure of integer residue rings. This allows us to provide a novel and improved Singleton-like bound in the Lee metric over integer residue rings. For all the bounds we discuss the density of their optimal codes. Originally, the Lee metric has been introduced over a $q$-ary alphabet to cope with phase shift modulation. We consider two channel models in the Lee metric. The first is a memoryless channel matching to the Lee metric under the decoding rule ``decode to the nearest codeword''. The second model is a block-wise channel introducing an error of fixed Lee weight, motivated by code-based cryptography where errors of fixed weight are added intentionally. We show that both channels coincide in the limit of large block length, meaning that their marginal distributions match. This distribution enables to provide bounds on the asymptotic growth rate of the surface and volume spectrum of spheres and balls in the Lee metric, and to derive bounds on the block error probability of the two channel models in terms of random coding union bounds. As vectors of fixed Lee weight are also of interest to cryptographic applications, we discuss the problem of scalar multiplication in the Lee metric in the asymptotic regime and in a finite-length setting. The Lee weight of a vector may be increased or decreased by the product with a nontrivial scalar. From a cryptographic view point this problem is interesting, since an attacker may be able to reduce the weight of the error and hence reduce the complexity of the underlying problem. The construction of a vector with constant Lee weight using integer partitions is analyzed and an efficient method for drawing vectors of constant Lee weight uniformly at random from the set of all such vectors is given. We then focus on regular LDPC code families defined over integer residue rings and analyze their performance with respect to the Lee metric. We determine the expected Lee weight enumerator for a random code in fixed regular LDPC code ensemble and analyze its asymptotic growth rate. This allows us to estimate the expected decoding error probability. Eventually, we estimate the error-correction performance of selected LDPC code families under belief propagation decoding and symbol message passing decoding and compare the performances. The thesis is concluded with an application of the results derived to code-based cryptography. Namely, we apply the marginal distribution to improve the yet known fastest Lee-information set decoding algorithm

Contributions to Confidentiality and Integrity Algorithms for 5G

The confidentiality and integrity algorithms in cellular networks protect the transmission of user and signaling data over the air between users and the network, e.g., the base stations. There are three standardised cryptographic suites for confidentiality and integrity protection in 4G, which are based on the AES, SNOW 3G, and ZUC primitives, respectively. These primitives are used for providing a 128-bit security level and are usually implemented in hardware, e.g., using IP (intellectual property) cores, thus can be quite efficient. When we come to 5G, the innovative network architecture and high-performance demands pose new challenges to security. For the confidentiality and integrity protection, there are some new requirements on the underlying cryptographic algorithms. Specifically, these algorithms should: 1) provide 256 bits of security to protect against attackers equipped with quantum computing capabilities; and 2) provide at least 20 Gbps (Gigabits per second) speed in pure software environments, which is the downlink peak data rate in 5G. The reason for considering software environments is that the encryption in 5G will likely be moved to the cloud and implemented in software. Therefore, it is crucial to investigate existing algorithms in 4G, checking if they can satisfy the 5G requirements in terms of security and speed, and possibly propose new dedicated algorithms targeting these goals. This is the motivation of this thesis, which focuses on the confidentiality and integrity algorithms for 5G. The results can be summarised as follows.1. We investigate the security of SNOW 3G under 256-bit keys and propose two linear attacks against it with complexities 2172 and 2177, respectively. These cryptanalysis results indicate that SNOW 3G cannot provide the full 256-bit security level. 2. We design some spectral tools for linear cryptanalysis and apply these tools to investigate the security of ZUC-256, the 256-bit version of ZUC. We propose a distinguishing attack against ZUC-256 with complexity 2236, which is 220 faster than exhaustive key search. 3. We design a new stream cipher called SNOW-V in response to the new requirements for 5G confidentiality and integrity protection, in terms of security and speed. SNOW-V can provide a 256-bit security level and achieve a speed as high as 58 Gbps in software based on our extensive evaluation. The cipher is currently under evaluation in ETSI SAGE (Security Algorithms Group of Experts) as a promising candidate for 5G confidentiality and integrity algorithms. 4. We perform deeper cryptanalysis of SNOW-V to ensure that two common cryptanalysis techniques, guess-and-determine attacks and linear cryptanalysis, do not apply to SNOW-V faster than exhaustive key search. 5. We introduce two minor modifications in SNOW-V and propose an extreme performance variant, called SNOW-Vi, in response to the feedback about SNOW-V that some use cases are not fully covered. SNOW-Vi covers more use cases, especially some platforms with less capabilities. The speeds in software are increased by 50% in average over SNOW-V and can be up to 92 Gbps.Besides these works on 5G confidentiality and integrity algorithms, the thesis is also devoted to local pseudorandom generators (PRGs). 6. We investigate the security of local PRGs and propose two attacks against some constructions instantiated on the P5 predicate. The attacks improve existing results with a large gap and narrow down the secure parameter regime. We also extend the attacks to other local PRGs instantiated on general XOR-AND and XOR-MAJ predicates and provide some insight in the choice of safe parameters

LIPIcs, Volume 274, ESA 2023, Complete Volume

LIPIcs, Volume 274, ESA 2023, Complete Volum

Asteroseismology and pulsation timing of the A-type stars observed by Kepler.

The A-type stars are arguably some of the most diverse stars found across the HR diagram, encompassing a wide range of physics, including rotation, pulsation, magnetic interactions, and chemical peculiarities. In this thesis, I develop a series of frameworks and tools to investigate a subset of the A-type stars: the delta Scuti and rapidly oscillating Ap (roAp) type stars, primarily using data from the Kepler and TESS space missions. I discuss the roAp stars within the context of the Kepler mission and identify six new members by exploiting irregularities in the sampling cadence. I then provide methods for the precise calculation of luminosities for A-type stars and apply them to the Kepler delta Scuti sample to improve the observational instability strip. I extend this work to a new class of young, high frequency delta Scuti stars discovered in the TESS data, which possess stable and regularly spaced modes, opening them up as potential candidates for mode identification via asteroseismology. I develop a framework for analysing delta Scuti stars in binary systems, through timing of their pulsations, and provide an open-source package to facilitate their analysis. Following this, I search for transits around the delta Scuti stars by iteratively subtracting their pulsations and identify three possible candidates in the Kepler data. Finally, I discuss the eclipsing binaries in the context of the inverse problem, and detail tested methods to rapidly obtain orbital parameters from the light curve with no prior knowledge