Continuous and transparent multimodal authentication: reviewing the state of the art

Individuals, businesses and governments undertake an ever-growing range of activities online and via various Internet-enabled digital devices. Unfortunately, these activities, services, information and devices are the targets of cybercrimes. Verifying the user legitimacy to use/access a digital device or service has become of the utmost importance. Authentication is the frontline countermeasure of ensuring only the authorized user is granted access; however, it has historically suffered from a range of issues related to the security and usability of the approaches. They are also still mostly functioning at the point of entry and those performing sort of re-authentication executing it in an intrusive manner. Thus, it is apparent that a more innovative, convenient and secure user authentication solution is vital. This paper reviews the authentication methods along with the current use of authentication technologies, aiming at developing a current state-of-the-art and identifying the open problems to be tackled and available solutions to be adopted. It also investigates whether these authentication technologies have the capability to fill the gap between high security and user satisfaction. This is followed by a literature review of the existing research on continuous and transparent multimodal authentication. It concludes that providing users with adequate protection and convenience requires innovative robust authentication mechanisms to be utilized in a universal level. Ultimately, a potential federated biometric authentication solution is presented; however it needs to be developed and extensively evaluated, thus operating in a transparent, continuous and user-friendly manner

Forecasting robust value-at-risk estimates: Evidence from UK banks

In this paper, we present a novel approach for forecasting Value-at-Risk (VaR) by combining a Bayesian GARCH(1,1) model with Student's-t distribution for the underlying volatility models, vine copula functions to model dependence, and peaks-over-threshold (POT) method of extreme value theory (EVT) to model the tail behaviour of asset returns. We further propose a new approach for threshold selection in extreme value analysis, which we call a hybrid method. The empirical results and back-testing analysis show that the model captures VaR quite well through periods of calmness and crisis; therefore, it is suitable for use as a measure of risk. Our results also suggest that with a correct implementation of the VaR model, Basel III is not needed

Refining value-at-risk estimates using a Bayesian Markov-switching GJR-GARCH copula-EVT model

In this paper, we propose a model for forecasting Value-at-Risk (VaR) using a Bayesian Markov-switching GJR-GARCH(1,1) model with skewed Student’s-t innovation, copula functions and extreme value theory. A Bayesian Markov-switching GJR-GARCH(1,1) model that identifies non-constant volatility over time and allows the GARCH parameters to vary over time following a Markov process, is combined with copula functions and EVT to formulate the Bayesian Markov-switching GJR-GARCH(1,1) copula-EVT VaR model, which is then used to forecast the level of risk on financial asset returns. We further propose a new method for threshold selection in EVT analysis, which we term the hybrid method. Empirical and back-testing results show that the proposed VaR models capture VaR reasonably well in periods of calm and in periods of crisis

Velocity-space sensitivity of the time-of-flight neutron spectrometer at JET

The velocity-space sensitivities of fast-ion diagnostics are often described by so-called weight functions. Recently, we formulated weight functions showing the velocity-space sensitivity of the often dominant beam-target part of neutron energy spectra. These weight functions for neutron emission spectrometry (NES) are independent of the particular NES diagnostic. Here we apply these NES weight functions to the time-of-flight spectrometer TOFOR at JET. By taking the instrumental response function of TOFOR into account, we calculate time-of-flight NES weight functions that enable us to directly determine the velocity-space sensitivity of a given part of a measured time-of-flight spectrum from TOFOR

Relationship of edge localized mode burst times with divertor flux loop signal phase in JET

A phase relationship is identified between sequential edge localized modes (ELMs) occurrence times in a set of H-mode tokamak plasmas to the voltage measured in full flux azimuthal loops in the divertor region. We focus on plasmas in the Joint European Torus where a steady H-mode is sustained over several seconds, during which ELMs are observed in the Be II emission at the divertor. The ELMs analysed arise from intrinsic ELMing, in that there is no deliberate intent to control the ELMing process by external means. We use ELM timings derived from the Be II signal to perform direct time domain analysis of the full flux loop VLD2 and VLD3 signals, which provide a high cadence global measurement proportional to the voltage induced by changes in poloidal magnetic flux. Specifically, we examine how the time interval between pairs of successive ELMs is linked to the time-evolving phase of the full flux loop signals. Each ELM produces a clear early pulse in the full flux loop signals, whose peak time is used to condition our analysis. The arrival time of the following ELM, relative to this pulse, is found to fall into one of two categories: (i) prompt ELMs, which are directly paced by the initial response seen in the flux loop signals; and (ii) all other ELMs, which occur after the initial response of the full flux loop signals has decayed in amplitude. The times at which ELMs in category (ii) occur, relative to the first ELM of the pair, are clustered at times when the instantaneous phase of the full flux loop signal is close to its value at the time of the first ELM

(Eucoccidiorida: Cryptosporiidae) in calves: results of a longitudinal study in a dairy farm in Sfax, Tunisia

A longitudinal study was undertaken to determine the prevalence of Cryptosporidium in a dairy farm in Sfax, Tunisia. 480 faecal samples were obtained from 30 calves under one month of age. All faecal samples were analysed for Cryptosporidium oocysts by microscopic examination of smears stained by modified Ziehl Neelsen technique. The parasite was detected in 26 calves (86.7 %). Infection was significantly associated with diarrhoea. A molecular characterization, performed in seven calves, confirmed that isolates were C. parvum. This work is the first report on Cryptosporidium in calves in Tunisia

Prevalence of

1,001 faecal samples were obtained from 89 sheep (lambs and adult), 184 goats, 190 horses, 178 rabbits, 110 camels, 200 broiler chicken and 50 turkeys housed in farms from different localities in Tunisia. All samples were analysed for Cryptosporidium oocysts by microscopic examination of smears stained by modified Ziehl Neelsen technique. The parasite was detected in ten lambs and adult sheep (11.2 %) and nine broiler chicken (4.5 %). Molecular characterization, performed in four animals, identified C. bovis in three lambs and C. meleagridis in one broiler chicken. This work is the first report on Cryptosporidium in farm animals in Tunisia

Prevalence of Cryptosporidium

1,001 faecal samples were obtained from 89 sheep (lambs and adult), 184 goats, 190 horses, 178 rabbits, 110 camels, 200 broiler chicken and 50 turkeys housed in farms from different localities in Tunisia. All samples were analysed for Cryptosporidium oocysts by microscopic examination of smears stained by modified Ziehl Neelsen technique. The parasite was detected in ten lambs and adult sheep (11.2 %) and nine broiler chicken (4.5 %). Molecular characterization, performed in four animals, identified C. bovis in three lambs and C. meleagridis in one broiler chicken. This work is the first report on Cryptosporidium in farm animals in Tunisia