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Error Amplification in Code-based Cryptography
Code-based cryptography is one of the main techniques enabling cryptographic primitives in a post-quantum scenario. In particular, the MDPC scheme is a basic scheme from which many other schemes have been derived. These schemes rely on iterative decoding in the decryption process and thus have a certain small probability p of having a decryption (decoding) error.In this paper we show a very fundam
Grain-128AEADv2: Strengthening the Initialization Against Key Reconstruction
Properties of the Grain-128AEAD key re-introduction, as part of the cipher initialization, are analyzed and discussed. We consider and analyze several possible alternatives for key re-introduction and identify weaknesses, or potential weaknesses, in them. Our results show that it seems favorable to separate the state initialization, the key re-introduction, and the A/R register initialization into
Grain-128AEAD, Round 3 Tweak and Motivation
Weaknesses in the Grain-128AEAD key re-introduction, as part of thecipher initialization, are analyzed and discussed. We consider and analyzeseveral possible alternatives for key re-introduction and identify weaknesses, or potential weaknesses, in them. Our results show that it seemsfavorable to separate the state initialization, the key re-introduction, andthe A/R register initialization into thr
A Weighted Bit Flipping Decoder for QC-MDPC-based Cryptosystems
Physics informed stochastic grey-box model of the flow-front in a vacuum assisted resin transfer moulding process with missing data
Real-time fault monitoring and control of the Vacuum Assisted Resin Transfer Moulding production process requires knowledge of the position of the epoxy flow-front inside the mould. Therefore, a fast and accurate flow-front tracking system is highly prized. Physics-informed grey-box models deliver a good trade-off between high fidelity and data-driven black-box models for designing such a flow-fro
Relaxations for Non-Separable Cardinality/Rank Penalties
Rank and cardinality penalties are hard to handle in optimization frameworks due to non-convexity and discontinuity. Strong approximations have been a subject of intense study and numerous formulations have been proposed. Most of these can be described as separable, meaning that they apply a penalty to each element (or singular value) based on size, without considering the joint distribution. In t
Information Set Decoding with Soft Information and some cryptographic applications
The class of information set decoding algorithms is the best known way of decoding general codes, i.e. codes that admit no special structure, in the Hamming metric. Stern's algorithm is the origin of the most efficient algorithms in this class. In this paper we consider the same decoding problem but for a channel with soft information. We give a version of Stern's algorithm for a channel with soft
Fixed-point algorithms for frequency estimation and structured low rank approximation
We develop fixed-point algorithms for the approximation of structured matrices with rank penalties. In particular we use these fixed-point algorithms for making approximations by sums of exponentials, i.e., frequency estimation. For the basic formulation of the fixed-point algorithm we show that it converges to the solution of a related minimization problem, namely the one obtained by replacing th
Estimates of global, regional, and national incidence, prevalence, and mortality of HIV, 1980-2015 : the Global Burden of Disease Study 2015
BACKGROUND: Timely assessment of the burden of HIV/AIDS is essential for policy setting and programme evaluation. In this report from the Global Burden of Disease Study 2015 (GBD 2015), we provide national estimates of levels and trends of HIV/AIDS incidence, prevalence, coverage of antiretroviral therapy (ART), and mortality for 195 countries and territories from 1980 to 2015.METHODS: For countri
A Recommender System for User-Specific Vulnerability Scoring
With the inclusion of external software components in their software, vendors also need to identify and evaluate vulnerabilities in the components they use. A growing number of external components makes this process more time-consuming, as vendors need to evaluate the severity and applicability of published vulnerabilities. The CVSS score is used to rank the severity of a vulnerability, but in its
A Recommender System for User-specific Vulnerability Scoring (full version)
With the inclusion of external software components in their software, vendors also need to identify and evaluate vulnerabilities in the components they use.A growing number of external components makes this process more time-consuming, as vendors need to evaluate the severity and applicability of published vulnerabilities.The CVSS score is used to rank the severity of a vulnerability, but in its s
Pregnancy outcome in women with gestational diabetes – A longitudinal study of changes in demography and treatment modalities
Introduction: Gestational diabetes is on the rise and demographics are changing in many countries due to increased migration. Simultaneously, the treatment of gestational diabetes in our clinic has shifted towards metformin with substantially less insulin treatment. The aim was to study the impact of these changes on metabolic control and pregnancy outcome by comparing women diagnosed with gestati
Digestion of triacylgycerols containing longchain polyenoic fatty acids in vitro by colipase dependent lipase and human milk bile salt stimulated lipase
To assess the role of human milk bile salt-stimulated lipase (BSSL) in the digestion of polyunsaturated ester bonds of triacylglycerols, hydrolysis of docosahexaenoic acid (22:6(n − 3)) ester bonds was compared to that of oleic acid (18:1(n − 9)) or arachidonic acid (20:4(n − 6)) esters. As model substrates, we used rat chylomicrons obtained after feeding human milk fat globules and radiolabeled f
Contributions to Preventive Measures in Cyber Security
Organizations and individuals maintain and use an ever increasing amount of computer systems, either deployed locally, or in the cloud.These systems often store and handle vast amounts of data, some of which is sensitive and should be kept private.Regardless of where the data is located, there is a need to prevent data from falling into the wrong hands.To this end, this dissertation presents contr
Software Defined Networking for Emergency Traffic Management in Smart Cities
Vehicle traffic management is becoming more complex due to increased traffic density in cities. Novel solutions are necessary for emergency vehicles, which despite growing congestion must be able to quickly reach their destination. Emergency vehicles are usually equipped with transmitters to control the traffic lights on their path and warn other vehicles with sirens. Transmitters are operated man
Energy-Optimal Data Aggregation and Dissemination for the Internet of Things
Established approaches to data aggregation in wirelesssensor networks (WSNs) do not cover the variety of new usecases developing with the advent of the Internet of Things. In particular,the current push towards fog computing, in which control,computation, and storage are moved to nodes close to the networkedge, induces a need to collect data at multiple sinks, ratherthan the single sink typically
Non-convex Rank/Sparsity Regularization and Local Minima
This paper considers the problem of recovering either a low rank matrix or a sparse vector from observations of linear combinations of the vector or matrix elements. Recent methods replace the non-convex regularization with ℓ1 or nuclear norm relaxations. It is well known that this approach recovers near optimal solutions if a so called restricted isometry property (RIP) holds. On the other hand i
A Non-convex Relaxation for Fixed-Rank Approximation
This paper considers the problem of finding a low rank matrix from observations of linear combinations of its elements. It is well known that if the problem fulfills a restricted isometry property (RIP), convex relaxations using the nuclear norm typically work well and come with theoretical performance guarantees. On the other hand these formulations suffer from a shrinking bias that can severely
Fast Laplace Transforms for the Exponential Radon Transform
The Fourier slice theorem for the standard Radon transform generalizes to a Laplace counterpart when considering the exponential Radon transform. We show how to use this fact in combination with algorithms for the unequally spaced fast Laplace transform to construct fast and accurate methods for computing both the forward exponential Radon transform and the corresponding back-projection operator.
