Authentication
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A common Authentication and Authorisation Infrastructure (AAI) that would allow single sign-on to services has been identified as a key enabler for European bioinformatics. ELIXIR AAI is an ELIXIR service portfolio for authenticating researchers to ELIXIR services and assisting these services on user privileges during research usage. It relieves the scientific service providers from managing the user identities and authorisation themselves, enables the researcher to have a single set of credentials to all ELIXIR services and supports meeting the requirements imposed by the data protection laws. ELIXIR AAI was launched in late 2016 and is part of the ELIXIR Compute platform portfolio. By the end of 2017 the number of users reached 1000, while the number of relying scientific services was 36. This paper presents the requirements and design of the ELIXIR AAI and the policies related to its use, and how it can be used for serving some example services, such as document management, social media, data discovery, human data access, cloud compute and training services.
- MeSH
- biomedicínský výzkum metody MeSH
- lidé MeSH
- software * MeSH
- systémy řízení databází * MeSH
- uživatelské rozhraní počítače MeSH
- výpočetní biologie metody MeSH
- výzkumní pracovníci MeSH
- zabezpečení počítačových systémů * MeSH
- Check Tag
- lidé MeSH
- Publikační typ
- časopisecké články MeSH
- práce podpořená grantem MeSH
Cíle: Cílem této práce je navrhnout vylepšenou metodu autentizace pro biomedicínu založenou na analýze behaviorálních biometrických metod používaných v soucasnosti. Metody: Práce poskytuje strucnou definici identifikace, autentizace a biometrických charakteristik. Hlavní cást práce se zabývá dynamikou stisku pocítacových kláves, jejími výhodami, nevýhodami a aplikacemi v biomedicíne. Dynamika stisku pocítacových kláves je následne navržena jako zajímavá behaviorální charakteristika pro použití v pocítacové bezpecnosti, která doposud není široce používaná. Výsledky: Výsledkem práce bude nový soubor metod, který umožní optimální multifaktorovou autentizaci z hlediska pohodlí, nákladu a spolehlivosti. Záver: Cílem tohoto príspevku je soustredit se na dostupné informace o dynamice stisku pocítacových kláves.
Objectives: The goal of this work is to suggest an improved authentication method for biomedicine based on analysis of currently used behavioural biometric methods. Methods: A brief definition of identification, authentication and biometric characteristics is provided. The main part of the work focuses on keystroke dynamics, its advantages, disadvantages and applications in biomedicine. Keystroke dynamics is then proposed as an interesting behavioural biometric characteristic for use in computer security not being widely used so far. Results: The result of the work will be a new set of methods, which allows optimal multi-factor authentication method regarding its comfort, cost and reliability. Conclusions: The purpose of this paper is to focus on the available information about keystroke dynamics.
A combination of direct analysis in real time (DART) ionization coupled to time-of-flight mass spectrometry (TOFMS) and chemometrics was used for animal fat (lard and beef tallow) authentication. This novel instrumentation was employed for rapid profiling of triacylglycerols (TAGs) and polar compounds present in fat samples and their mixtures. Additionally, fat isolated from pork, beef, and pork/beef admixtures was analyzed. Mass spectral records were processed by principal component analysis (PCA) and stepwise linear discriminant analysis (LDA). DART-TOFMS profiles of TAGs were found to be more suitable for the purpose of discrimination among the examined fat types as compared to profiles of polar compounds. The LDA model developed using TAG data enabled not only reliable classification of samples representing neat fats but also detection of admixed lard and tallow at adulteration levels of 5 and 10% (w/w), respectively. The presented approach was also successfully applied to minced meat prepared from pork and beef with comparable fat content. Using the DART-TOFMS TAG profiles of fat isolated from meat mixtures, detection of 10% pork added to beef and vice versa was possible.
- MeSH
- diskriminační analýza MeSH
- hmotnostní spektrometrie přístrojové vybavení metody MeSH
- maso analýza MeSH
- prasata MeSH
- řízení kvality MeSH
- skot MeSH
- triglyceridy analýza MeSH
- tuky chemie MeSH
- zvířata MeSH
- Check Tag
- skot MeSH
- zvířata MeSH
- Publikační typ
- časopisecké články MeSH
- hodnotící studie MeSH
- práce podpořená grantem MeSH
Mandatory disclosure of the species identity, production method, and geographical origin are embedded in the regulations and traceability systems, governing international seafood trade. A high-resolution mass spectrometry-based metabolomics approach could simultaneously authenticate the species identity and geographical origin of commercially important shrimps. The highly innovative approach spared the need for multiple testing methods which are in routine use currently. A robust chemometric model, developed using the metabolite fingerprint dataset, could accurately predict the species identity of the shrimp samples. Subsequently, species-specific biomarkers were discovered and a tandem mass spectrometry method for authentication of the species was developed. Two other chemometric models from the metabolomics experiment accurately predicted the geographical origin of king prawns and tiger prawns. The study has shown for the first time that food-metabolomics along with chemometrics can simultaneously check for multiple seafood fraud issues in the global seafood supply-chain.
- MeSH
- analýza potravin metody MeSH
- biologické markery analýza chemie MeSH
- Decapoda (Crustacea) chemie klasifikace MeSH
- druhová specificita MeSH
- metabolomika * MeSH
- potrava z moře (živočišná) analýza MeSH
- tandemová hmotnostní spektrometrie MeSH
- zeměpis MeSH
- zvířata MeSH
- Check Tag
- zvířata MeSH
- Publikační typ
- časopisecké články MeSH
Ultra-high-performance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry (MS) and an alternative technology represented by direct analysis in real time coupled with quadrupole time-of-flight MS were investigated for metabolic fingerprinting of 343 red and white wine samples. Direct injection of pure wine and an extraction procedure optimized for isolation of polyphenols were used to compare different analytical and data handling strategies. After data processing and data pretreatment, principal component analysis was initially used to explore the data structure. Initially, the unsupervised models revealed a notable clustering according to the grape varieties, and therefore supervised orthogonal partial least squares discriminant analysis models were created and validated for separation of red and white wines according to the grape variety. The validated orthogonal partial least squares discriminant analysis models based on data (ions) recorded in positive ionization mode were able to classify correctly 95% of samples. In parallel, authentication parameters, such as origin and vintage, were evaluated, and they are discussed. A tentative identification of markers was performed using accurate mass measurement of MS and MS/MS spectra, different software packages and different online libraries. In this way, different flavonol glucosides and polyphenols were identified as wine markers according to the grape varieties.
The rapidly growing demand for organic food requires the availability of analytical tools enabling their authentication. Recently, metabolomic fingerprinting/profiling has been demonstrated as a challenging option for a comprehensive characterisation of small molecules occurring in plants, since their pattern may reflect the impact of various external factors. In a two-year pilot study, concerned with the classification of organic versus conventional crops, ambient mass spectrometry consisting of a direct analysis in real time (DART) ion source and a time-of-flight mass spectrometer (TOFMS) was employed. This novel methodology was tested on 40 tomato and 24 pepper samples grown under specified conditions. To calculate statistical models, the obtained data (mass spectra) were processed by the principal component analysis (PCA) followed by linear discriminant analysis (LDA). The results from the positive ionisation mode enabled better differentiation between organic and conventional samples than the results from the negative mode. In this case, the recognition ability obtained by LDA was 97.5% for tomato and 100% for pepper samples and the prediction abilities were above 80% for both sample sets. The results suggest that the year of production had stronger influence on the metabolomic fingerprints compared with the type of farming (organic versus conventional). In any case, DART-TOFMS is a promising tool for rapid screening of samples. Establishing comprehensive (multi-sample) long-term databases may further help to improve the quality of statistical classification models.
There are many people who suffer from some of the skin diseases. These diseases have a strong influence on the process of fingerprint recognition. People with fingerprint diseases are unable to use fingerprint scanners, which is discriminating for them, since they are not allowed to use their fingerprints for the authentication purposes. First in this paper the various diseases, which might influence functionality of the fingerprint-based systems, are introduced, mainly from the medical point of view. This overview is followed by some examples of diseased finger fingerprints, acquired both from dactyloscopic card and electronic sensors. At the end of this paper the proposed fingerprint image enhancement algorithm is described.
