The goal of my diploma thesis was finding a suitable method for unifying score values from various protein identification search tools in MS/MS mass spectrometry into one single score value. Data coming from the output of mass spectrometer are processed in two independent search tools Mascot and X!Tandem. These were selected especially for their wide usage in proteomic labs. Both results are evaluated through newly designed function and unified by single valued score clearly identifying found proteins. Newly designed scoring value is called Matascore and function producing this score was implemented in MATLAB. Function and its results were successfully tested by real data available in public databases on the Internet.

The goal of the thesis is the finger-print authentication support within the Linux operating system and the K Desktop Environment (KDE). Theoretical part of the thesis firstly explains main IT security terms and ways to proof the identity. Secondly it describes biometric systems and types of processed biometric characteristics. Lastly the features of finger-prints, their markants as well as types of scanners used in scanning the finger-prints and ways to analyze the scanned material have been elaborated. Practical solution part of the thesis develops and establishes finger-print management application and plugin for KDM graphics login manager.

Heutzutage beeinflusst die Biometrie mehr und mehr unsere Leben. Diese Technologie soll uns Sicherheit und auch Bequemlichkeit erschaffen. Biometrische Systeme ersetzen jeden Tag ältere Sicherheitssysteme und die Firmen versprechen sich mehr Leistung zu bekommen. Aber trotzdem kann man über viele Bereiche der Biometrie sagen, dass sie noch zurückgeblieben sind. In meiner Arbeit analysiere ich den Zustand der ganzen biometrischen Industrie, ich lerne die neuesten Technologien kennen. Die Mängel dieser Industrie sind noch deutlich und es müssen noch viele Innovationen durchgesetzt werden. Ich widme mich meistens der Sicherheit der biometrischen Systeme, konkret orientiere ich mich auf die Fingerabdruckstechnologie. Nach der Analyse der neuesten Angriffe und Sicherheitsvorgänge, werte ich die Technik der Erkennung der feinen Hautbewegungen der Fingerspitzen aus.

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In der vorliegenden Arbeit wurden 2460 Viertelgemelksproben aus 16 hessischen Milcherzeugerbetrieben untersucht. 115 S. canis-Isolate konnten gefunden und auf ihre morphologischen, biochemischen und bei molekularbiologischen Eigenschaften untersucht werden. Die Isolate stammten von Viertelgemelksproben bzw. Tankproben, die zu einem oder mehreren Zeitpunkten in den Betrieben genommen wurden. Die Untersuchung der biochemischen Eigenschaften erbrachte 24 verschiedene Reaktionsmuster. Der Vergleich dieser 24 Biotypen mit einem S. canis-Referenzstamm mittels tDNA-PCR und 16S-RNA-PCR ergab eine völlige Übereinstimmung (100%) und damit eine sichere Spezies-Identifizierung. Zur Aufklärung epidemiologischer Zusammenhänge und zur Intra-Spezies-Identifizierung wurde von allen 115 Isolaten mittels PFGE nach Makrorestriktionsverdau mit SmaI ein DNA-Fingerprint erstellt. Dabei ergaben sich 21 verschiedene Restriktionsmuster. Von den 21 nach Makrorestriktion mit Sma I und anschließender PFGE unterscheidbaren Restriktionsmustern wurde je ein Isolat zur Bestimmung der Differenzierungsfähigkeit der Restriktionsenzyme Cla I und Apa I sowie der RAPD-PCR weitergehend untersucht. Für die Beurteilung epidemiologischer Zusammenhänge bei S. canis erwies sich die PFGE nach Makrorestriktion mittels Sma I als die differenzierteste Variante. Die mittels PFGE nach Makrorestriktionsverdau mit Sma I durchgeführten Untersuchungen der 115 Isolate zeigten, dass zu einem Probennahme-Termin gewonnene Isolate identisch waren; vom gleichen Betrieb zu unterschiedlichen Zeiten entnommene Proben zeigten z.T. deutliche Unterschiede, und bei Isolaten von verschiedenen Betrieben konnten keine Verwandtschaftsbeziehungen nachgewiesen werden. Aufgrund dieser genotypischen Eigenschaften der Kulturen konnte gezeigt werden, dass es sich bei durch S. canis verursachte Mastitiden um ein infektiöses Bestandsproblem handelt, bei dem der Erreger von Viertel zu Viertel und von Kuh zu Kuh übertragen wird.

Denna studie undersöker anställdas inställning till BA som MFA-metod på svenska SMF, även vilken BA-metod som anses lämpligast för användning. Tidigare studier har främst fokuserat på större organisationer och företag med kvantitativa forskningsmetoder. Därav har denna studie valt att undersöka SMF med en kvalitativ inriktning i formen av en semistrukturerad intervjustudie. Studien genomförde totalt nio intervjuer från varierande företag med respondenter aven mängd olika arbetsroller. Utifrån dessa intervjuer kunde flera teman identifieras, dessa användes för att dra slutsatser kring användarens inställning och vilken BA-metod som föredras i företagskontext. Teman som identifierades utgjorde grunden förde anställdas inställning, exempelvis vilka positiva och negativa aspekter de anställda kunde se med BA som MFA. Resultaten visade att de anställda generellt sett var positivt inställda till BA som MFA-metod och att de flesta kunde tänka sig implementera detta på sin arbetsplats. Av fingeravtryck, röstigenkänning,ansiktsigenkänning och irisskanning föredrog respondenterna fingeravtryck som BA-metod i företagskontext. Studien valde att inte fokusera på företag som redan implementerat BA som MFA. Applikationer och program som anställda använder där BA erbjuds anses inte som att företaget implementerat BA som MFA. / This study examines employees' attitudes towards BA (Biometric Authentication) as an MFA (Multi-Factor Authentication) method at Swedish SMEs, as well as which BA method is considered most suitable for use. Previous studies have focused on larger organizations and companies with quantitative research methods. Therefore, this study has chosen to examine SMEs with a qualitative focus by conducting semistructured interviews. The study conducted a total of nine interviews from various companies with respondents from a variety of work roles. Based on these interviews, several themes could be identified, these were used to draw conclusions about the employees’ attitude and which BA method is preferred in a business context. Themes that were identified formed the basis for the employees' attitude, for example what positive and negative aspects the employees could see with BA as MFA. The results showed that the employees were generally positive about BA as an MFA method and that most could imagine implementing this in their workplace. Focusing on fingerprints, voice recognition, face recognition and iris scanning, the respondents preferred fingerprints as a BA method. The study chose not to focus on companies that have already implemented BA as MFA. Applications and programs that employees use where BA is offered are not considered that the company has implemented BA as MFA.

The growing interest in the Internet of Things (IoT) has led to predictions claiming that by 2020 we can expect to be surrounded by 50 billion Internet connected devices. With more entry points to a network, adversaries can potentially use IoT devices as a stepping stone for attacking other devices connected to the network or the network itself. Information security relies on cryptographic primitives that, in turn, depend on secret keys. Furthermore, the issue of Intellectual property (IP) theft in the field of Integrated circuit (IC) design can be tackled with the help of unique device identifiers. Physical unclonable functions (PUFs) provide a tamper-resilient solution for secure key storage and fingerprinting hardware. PUFs use intrinsic manufacturing differences of ICs to assign unique identities to hardware. Arbiter PUFs utilise the differences in delays of identically designed paths, giving rise to an unpredictable response unique to a given IC. This thesis explores the statistical properties of Boolean functions induced by arbiter PUFs. In particular, this empirical study looks into the distribution of induced functions. The data gathered shows that only 3% of all possible 4-variable functions can be induced by a single 4 stage arbiter PUF. Furthermore, some individual functions are more than 5 times more likely than others. Hence, the distribution is non-uniform. We also evaluate alternate PUF designs, improving the coverage vastly, resulting in one particular implementation inducing all 65,536 4-variable functions. We hypothesise the need for n XORed PUFs to induce all 22n possible n-variable Boolean functions.

Quantitative structure-activity relationship (QSAR) models based on machine learning algorithms are powerful tools to expedite drug discovery processes and therapeutics development. Given the cost in acquiring large-sized training datasets, it is useful to examine if QSAR analysis can reasonably predict drug activity with only a small-sized dataset (size < 100) and benchmark these small-dataset QSAR models in application-specific studies. To this end, here we present a systematic benchmarking study on small-dataset QSAR models built for prediction of effective Wnt signaling inhibitors, which are essential to therapeutics development in prevalent human diseases (e.g., cancer). Specifically, we examined a total of 72 two-dimensional (2D) QSAR models based on 4 best-performing algorithms, 6 commonly used molecular fingerprints, and 3 typical fingerprint lengths. We trained these models using a training dataset (56 compounds), benchmarked their performance on 4 figures-of-merit (FOMs), and examined their prediction accuracy using an external validation dataset (14 compounds). Our data show that the model performance is maximized when: 1) molecular fingerprints are selected to provide sufficient, unique, and not overly detailed representations of the chemical structures of drug compounds; 2) algorithms are selected to reduce the number of false predictions due to class imbalance in the dataset; and 3) models are selected to reach balanced performance on all 4 FOMs. These results may provide general guidelines in developing high-performance small-dataset QSAR models for drug activity prediction.

Background: Structure-based drug repositioning has emerged as a promising alternative to conventional drug development. Regardless of the many success stories reported over the past years and the novel breakthroughs on the AI-based system AlphaFold for structure prediction, the availability of structural data for protein–drug complexes remains very limited. Whereas the chemical libraries contain millions of drug compounds, the vast majority of them do not have structures to crystallized targets,and it is, therefore, impossible to characterize their binding to targets from a structural view. However, the concept of building blocks offers a novel perspective on the structural problem. A drug compound is considered a complex of small chemical blocks or fragments, which confer the relevant properties to the drug and have a high proportion of functional groups involved in protein binding. Based on this, we propose a novel approach to expand the scope of structure-based repositioning approaches by transferring the structural knowledge from a fragment to a compound level. - Results: We fragmented over 100,000 compounds in the Protein Data Bank (PDB) and characterized the structural binding mode of 153,000 fragments to their crystallized targets. Using the fragment’s data, we were able to artificially reconstruct the binding mode of over 7,800 complexes between ChEMBL compounds and their known targets, for which no structural data is available. We proved that the conserved binding tendency of fragments, when binding to the same targets, highly influences the drug’s binding specificity and carries the key information to reconstruct full drugs binding mode. Furthermore, our approach was able to reconstruct multiple compound-target pairs at optimal thresholds and high similarity to the actual binding mode. - Conclusions: Such reconstructions are of great value and benefit structure-based drug repositioning since they automatically enlarge the technique’s scope and allow exploring the so far ‘unexplored compounds’ from a structural perspective. In general, the transfer of structural information is a promising technique that could be applied to any chemical library, to any compound that has no crystal structure available in PDB, and even to transfer any other feature that may be relevant for the drug discovery process and that due to data limitations is not yet fully available. In that sense, the results of this work document the full potential of structure-based screening even beyond PDB.

Computer security is a growing field in the IT industry. One of the important aspects of the computer security is authentication. Using passwords (something you know) is one of the most common ways of authentications. But passwords have proven to provide weak level of security as they can be easily compromised. Some other ways of authenticating a user are using physical tokens, (something you possess) and biometrics, (something you are). Using any one of these techniques to secure a system always has its own set of threats. One way to make sure a system is secure is to use multiple factors to authenticate. One of the ways to use multiple factors is to use all the three factors of authentication, something you possess, something you are and something you know. This thesis discusses about different ways of authentication and implements a system using three factor authentication. It takes many security aspects of the system into consideration while implementing it, to make it secure.