On the Security of HB# against a Man-in-the-Middle Attack

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In this thesis, we explore cryptographic protocols in three seemingly counter-intuitive settings or properties and attempt to achieve secure protocols under these settings. First, we consider the problem of future proofing of classical signatures against ...

Electrochemical Impedance Spectroscopy (EIS) and Equivalent Circuit Models (ECMs) are widely used to characterize the impedance and estimate parameters of electrochemical systems such as batteries. We use a generic ECM with ten parameters grouped to model ...

The ITER Electron Cyclotron Resonance Heating and Current Drive (ECRH&CD) system relies on 1 MW 170 GHz Gyrotrons to provide the mm-wave power needed for plasma heating, current drive, and magneto-hydrodynamic control. The design and modeling of the contro ...

Side-channel attacks exploit a physical observable originating from a cryptographic device in order to extract its secrets. Many practically relevant advances in the field of side-channel analysis relate to security evaluations of cryptographic functions a ...

The establishment of a single European day-ahead market has accomplished the integration of the regional day-ahead markets. However, reserve provision and activation remain an exclusive responsibility of regional operators. This limited spatial coordinatio ...

The early time high altitude electromagnetic pulse conducted environment calculation is revisited by using the transmission line (TL) theory and including high-frequency corrections that were not present in the earlier studies. Waveform salient parameters, ...

This paper deals with the mathematical model that describes the function of the human heart. More specifically, it addresses the equations that express the electromechanical process, that is the mechanical deformation (contraction and relaxation) of the he ...

Many engineering fields rely on frequency-domain dynamical systems for the mathematical modeling of physical (electrical/mechanical/etc.) structures. With the growing need for more accurate and reliable results, the computational burden incurred by frequen ...

The spread of coronavirus disease 2019 (COVID-19) in Italy prompted drastic measures for transmission containment. We examine the effects of these interventions, based on modeling of the unfolding epidemic. We test modeling options of the spatially explici ...

This study evaluates and compares several machine learning methods on the effects of different parameters in lead adsorption capacity. pH, contact time, adsorbent dosage and initial lead concentration were considered as inputs and adsorption capacity was r ...

The importance of additive manufacturing, also known as 3D printing, has grown exponentially in the recent years thanks to its high flexibility to manufacture intricate parts. This process can be divided into many different sub-categories, depending on the ...

Somatosensory thalamocortical (TC) neurons from the ventrobasal (VB) thalamus are central components in the flow of sensory information between the periphery and the cerebral cortex, and participate in the dynamic regulation of thalamocortical states inclu ...

This study evaluates and compares several machine learning methods on the effects of different parameters in the hydrothermal carbonisation (HTC) process of macroalgae Sargassum horneri. Reaction temperature, residence time, biomass particle size, the amou ...

We introduce a sequence-dependent coarse-grain model of double-stranded DNA with an explicit description of both the bases and the phosphate groups as interacting rigid-bodies. The model parameters are trained on extensive, state-of-the-art large scale mol ...

Proper modeling of stochastic errors in inertial sensors plays a crucial role in the achievable quality of GNSS-INS integration especially with low-cost inertial sensors. Generalized Method of Wavelet Moments (GMWM) can model the underlying process for suc ...

What-if analysis is a data-intensive exploration to inspect how changes in a set of input parameters of a model influence some outcomes. It is motivated by a user trying to understand the sensitivity of a model to a certain parameter in order to reach a se ...

Localizing the source of an epidemic is a crucial task in many contexts, including the detection of malicious users in social networks and the identification of patient zeros of disease outbreaks. The difficulty of this task lies in the strict limitation ...

A non-intrusive reduced basis (RB) method is proposed for parametrized nonlinear structural analysis undergoing large deformations and with elasto-plastic constitutive relations. In this method, a reduced basis is constructed from a set of full-order snaps ...

The estimation of the apparent axon diameter (AAD) via diffusion MRI is affected by the incoherent alignment of single axons around its axon bundle direction, also known as orientational dispersion. The simultaneous estimation of AAD and dispersion is chal ...

On the Security of HB# against a Man-in-the-Middle Attack

Chattez avec Graph Search

Cryptography Under Counter-Intuitive Settings

On the use of Cramér-Rao Lower Bound for least-variance circuit parameters identification of Li-ion cells

Sensitivity Analysis of the Lumped Thermal Model of the EU 170 GHz Gyrotron Magnetron Injection Gun

The Side-channel Metrics Cheat Sheet

Enabling inter-area reserve exchange through stable benefit allocation mechanisms *

Revisiting the Calculation of the Early Time HEMP Conducted Environment

Mathematical and numerical models for the cardiac electromechanical function

Model order reduction based on functional rational approximants for parametric PDEs with meromorphic structure

Spread and dynamics of the COVID-19 epidemic in Italy: Effects of emergency containment measures

Investigation of effective processes parameters on lead (II) adsorption from wastewater by biochar in mild air oxidation pyrolysis process

Operando X-ray diffraction during laser 3D printing: from machine design to experiments and computer simulations

Experimentally-constrained biophysical models of tonic and burst firing modes in thalamocortical neurons

Physico-chemical properties prediction of hydrochar in macroalgae Sargassum horneri hydrothermal carbonisation

A sequence-dependent coarse-grain model of B-DNA with explicit description of bases and phosphate groups parametrised from large scale Molecular Dynamics simulations

Optimal Stochastic Sensor Error Modeling based on Actual Impact on Quality of GNSS-INS Integrated Navigation

Exploring Data Partitions for What-if Analysis

Localizing the Source of an Epidemic Using Few Observations

What-if Analysis with Conflicting Goals: Recommending Data Ranges for Exploration

Reduced order modeling for nonlinear structural analysis using Gaussian process regression

Orientation-Dispersed Apparent Axon Diameter via Multi-Stage Spherical Mean Optimization