This master's thesis with the usage of the system for the content managing - the DotNetNuke system as an editorial system. It describes all options and features of the DotNetNuke system. On its basis of the system's features there have been made proposals for extensions which, when implemented, will let the DotNetNuke system to be used as full-value editorial system.

Mit HylaFAX+ wurde eine gute Grundlage für eine neue Faxlösung an der Technischen Universität Chemnitz gefunden. Durch die vielen Schnittstellen, die HylaFAX+ bietet, konnte es um fehlende Funktionen erweitert werden, sodass es den gestellten Anforderungen entspricht. Auf Basis dieser Arbeit, kann unter Berücksichtigung der Richtlinien des URZ, eine neue Faxlösung implementiert werden, welche den XMediusFAX-Server ablöst. Das FoIP-Gateway nimmt E-Mails entgegen und verarbeitet diese inklusive Anhang, dieser kann eine PDF, ein Word Dokument oder ein Bilddokument in den Formaten JPEG oder PNG sein. Bevor das Fax abgesendet wird, setzt ein Skript die richtige Faxnummer des Absenders ein und prüft ob der Absender die nötigen Rechte hat um ein Fax intern/national/international zu versenden. Die eigentliche Übertragung des Faxes erfolgt über das T.38 Protokoll, sollte der Empfänger dieses nicht beherrschen, wechselt die Faxlösung automatisch auf die Pass-Through Methode. Ist das Fax erfolgreich übertragen, erhält der Sender eine Sendebestätigung per E-Mail oder Ausdruck. Wird eine Faxnachricht empfangen, wird noch vor während der Rufannahme geprüft ob der Empfänger innerhalb des Universitätsnetzes existiert. Falls es die Empfängernummer nicht gibt, wird der Anruf augenblicklich beendet. Ist die Faxnummer einem Nutzer zugeordnet, ermittelt ein Pythonskript die E-Mailadresse des Empfängers. Dieser erhält die Faxnachricht anschließend als PDF im Anhang einer E-Mail. Sollte im LDAP ein Drucker hinterlegt sein bekommt der Nutzer einen Ausdruck auf dem eingestellten Drucker.

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Artifact-based research provides a mechanism whereby researchers may study the creation of software yet avoid many of the difficulties of direct observation and experimentation. Open source software forges are of great value to the software researcher, because they expose many of the artifacts of software development. However, many challenges affect the quality of artifact-based studies, especially those studies examining software evolution. This thesis addresses one of these threats: the presence of very large commits, which we refer to as "Cliff Walls." Cliff walls are a threat to studies of software evolution because they do not appear to represent incremental development. In this thesis we demonstrate the existence of cliff walls in open source software projects and discuss the threats they present. We also seek to identify key causes of these monolithic commits, and begin to explore ways that researchers can mitigate the threats of cliff walls.

<p>Information about the conditions of specific fields and assets is critical for farm managers to make operational decisions. Location, rainfall, windspeed, soil moisture, and temperature are examples of metrics that influence the ability to perform certain tasks. Monitoring these events in real time and being able to store historical data can be done using Internet of Things (IoT) devices such as sensors. The abilities of this technology have previously been communicated, yet few farmers have adopted these connected devices into their work. A lack of reliable internet connection, the high annual cost of current on-market systems, and a lack of technical awareness have all contributed to this disconnect. One technology that can better meet the demand of farmers is LoRaWAN because of its long range, low power, and low cost. To assist farmers in implementing this technology on their farms the goal was to build a LoRaWAN network with several sensors to measure metrics such as weather data, distribute these systems locally, and provide context to the operation of IoT networks. By leveraging readily available commercial hardware and opens source software two examples of standalone networks were created with sensor data stored locally and without a dependence on internet connectivity. The first use case was a kit consisting of a gateway and small PC mounted to a tripod with 6 individual sensors and cost close to $2200 in total. An additional design was prepared for a micro-computer-based version using a Raspberry Pi, which made improvements to the original design. These adjustments included a lower cost and complication of hardware, software with more open-source community support, and cataloged steps to increase approachability. Given outside factors, the PC architecture was chosen for mass distribution. Over one year, several identical units were produced and given to farms, extension educators, and vocational agricultural programs. From this series of deployments, all units survived the growing season without damage from the elements, general considerations about the chosen type of sensors and their potential drawbacks were made, the practical observed average range for packet acceptance was 3 miles, and battery life among sensors remained usable after one year. The Pi-based architecture was implemented in an individual use case with instructions to assist participation from any experience level. Ultimately, this work has introduced individuals to the possibilities of creating and managing their own network and what can be learned from a reasonably simple, self-managed data pipeline.</p>

The BioChemical Library (BCL) cheminformatics toolkit is an application-based academic open-source software package designed to integrate traditional small molecule cheminformatics tools with machine learning-based quantitative structure-activity/ property relationship (QSAR/QSPR) modeling. In this pedagogical article we provide a detailed introduction to core BCL cheminformatics functionality, showing how traditional tasks (e.g., computing chemical properties, estimating druglikeness) can be readily combined with machine learning. In addition, we have included multiple examples covering areas of advanced use, such as reaction-based library design. We anticipate that this manuscript will be a valuable resource for researchers in computer-aided drug discovery looking to integrate modular cheminformatics and machine learning tools into their pipelines.

[pt] Este trabalho descreve a mineração de informações em linguagem natural a partir do repositório de projetos GitHub. É explicada como o conteúdo de projetos semelhantes dada uma busca por domínio podem ser úteis para o reuso de conhecimento, e assim, ajudar nas tarefas de Elicitação de Requisitos. Técnicas de mineração de textos, regularidades independentes do domínio, e os metadados de GitHub são os métodos utilizados para selecionar projetos relevantes e as informações dentro deles. Uma abordagem para atingir nossa meta utilizando pesquisa exploratória é explicada, bem como descrevemos os resultados alcançados. / [en] This work describes the mining of information in natural language from the GitHub repository. It is explained how the content of similar projects given a search domain can be useful for the reuse of knowledge, and thus help in the Requirements Elicitation tasks. Techniques of text mining, regularities independent from domain, and GitHub metadata are the methods used to select relevant projects and the information within them. One approach to achieve our goal is explained with an exploratory research and the results achieved.

This thesis presents a comprehensive security analysis of the Server-Server API of the Matrix protocol, providing a detailed examination of its vulnerabilities and contributing a significant body of knowledge to the cybersecurity field. The research focused exclusively on the Server-Server API of the Matrix protocol. Despite the testing of 2 vulnerabilities that did not succeed, the primary contribution of this work lies in the in-depth threat analysis and the identification of 16 critical, yet untested, vulnerabilities that may be probed in future research. The findings reveal that the Matrix protocol’s Server-Server API currently maintains a competent level of security. However, the uncovered vulnerabilities highlight the necessity for continuous and proactive security measures within its ongoing development. The practical implications of the identified vulnerabilities are substantial, with relevance extending to similar APIs in the broader digital communication landscape. The rigorous penetration testing methodology following rigorous standards, coupled with systematic documentation, ensures a trustworthy basis for the study’s conclusions. In essence, this thesis does not only answer the research question by identifying and documenting current security weaknesses within the Server-Server API but also establishes a methodological foundation for future security enhancement initiatives. By doing so, it adds valuable insights to the cybersecurity community, with implications for developers, researchers, and users alike, emphasizing the need for a persistent and vigilant approach to API security in the evolving digital era / Denna avhandling presenterar en omfattande säkerhetsanalys av Server-Server API:et för Matrix-protokollet, och bidrar med en utvärdering av dess sårbarheter och betydande kunskap till cybersäkerhetsområdet. Forskningen fokuserade uteslutande på Server-Server API:et för Matrix-protokollet. Trots penetrationstestningen av två sårbarheter som inte lyckades, ligger det primära bidraget från detta arbete i den djupgående hotanalysen och identifieringen av 16 kritiska, ännu otestade, sårbarheter som kan utforskas i framtida forskning. Resultaten visar att Matrix-protokollets Server-Server API för närvarande upprätthåller en bra säkerhetsnivå. De upptäckta sårbarheterna betonar dock nödvändigheten av kontinuerliga säkerhetsåtgärder inom dess pågående utveckling. De praktiska konsekvenserna av de identifierade sårbarheterna är betydande, med relevans som sträcker sig till liknande API:er i det bredare digitala kommunikationslandskapet. Den noggranna metodiken för penetrationstestning enligt strikta standarder, tillsammans med systematisk dokumentation, säkerställer en tillförlitlig grund för studiens slutsatser. I grund och botten svarar denna avhandling inte bara på forskningsfrågan genom att identifiera och dokumentera nuvarande säkerhetsbrister inom Server-Server API:et utan etablerar också en metodologisk grund för framtida säkerhetsförstärkningsinitiativ. Genom att göra detta tillför den värdefulla insikter till cybersäkerhetsgemenskapen, med implikationer för utvecklare, forskare och användare lika, vilket betonar behovet av en ihärdig och vaksam inställning till API-säkerhet i den utvecklande digitala eran.

In this thesis, we explored the possibility of introducing a few vulnerabilities to a separation kernel to increase its performance. We made modifications to S3K, an open-source separation kernel that is in the final stages of being designed. To test the viability of our modifications we benchmarked both the unmodified and the modified versions and compared the results. We changed the scheduler and the inter-process communication used for time sharing: we introduced side-channel vulnerabilities to allow the modified functionalities to complete their work faster. The changes to the scheduler increased performance notably when having a high scheduling overhead, but not so much with low overhead. The changes to the inter-process communication proved to have limited usefulness, as the default version was already rather quick, and the new version had the drawback of increasing the time needed for scheduling. We also tested our scheduler modifications in the inter-process communication benchmarks. This greatly improved performance in all scenarios, and it made our modifications to the inter-process communication slightly more viable. To see how our results held up in a scenario closer to a real use case we also implemented a simple cryptographic application and designed tests based on it. When we ran the tests with different combinations of including or excluding our modifications we got similar results to our previous benchmarks. Overall, our modifications to the scheduler seem like a promising change to the separation kernel, given that one is willing to introduce the side-channels that come with the changes. The modifications to the inter-process communication on the other hand are more questionable and are likely only useful in specific scenarios. / I detta arbete utforskade vi möjligheten att introducera några sårbarheter till en separationskärna för att öka dess prestanda. Vi modifierade S3K, en separationskärna med öppen källkod som är i slutstadiet av att designas. För att testa hur praktiskt användbara våra modifikationer var så körde vi benchmarks på både den ursprungliga versionen och den modifierade versionen och jämförde resultaten. Vi ändrade schemaläggaren och interprocesskommunikationen som används för att dela tid: sidokanalssårbarheter introducerades för att tillåta de ändrade funktionerna att göra färdigt sina arbeten snabbare. Ändringarna till schemaläggaren visade sig öka prestandan noterbart när man hade en hög schemaläggnings-overhead, men skillnaden var inte så stor med låg overhead. Ändringarna till interprocesskommunikationen visade sig ha begränsad användbarhet, då standardversionen redan var ganska snabb och den nya versionen hade nackdelen att den ökade schemaläggningstiden. Vi testade också våra schemaläggningsmodifikationer i våra benchmarks för interprocesskommunikationen. Detta ökade prestandan mycket i alla scenarion, och gjorde våra modifikationer till interprocesskommunikationen något mer praktiskt användbara. För att se hur våra resultat stod sig i ett mer verkligt scenario så implementerade vi också en simpel kryptografisk applikation, och utformade test runt den. När vi testade olika kombinationer av att inkludera eller exkludera våra modifikationer fick vi liknande resultat som vi fick i tidigare benchmarks. Överlag så verkar våra modifikationer till schemaläggaren lovande, givet att man är villig att introducera de sidokanalssårbarheter som kommer med ändringarna. Modifikationerna till interprocesskommunikationen är dock mer tveksamma, och är sannolikt bara användbara i specifika scenarion.

The use of Open Source Software is becoming more and more popular, but it comes with the risk of importing vulnerabilities in private codebases. Security patches, providing fixes to detected vulnerabilities, are vital in protecting against cyber attacks, therefore being able to apply all the security patches as soon as they are released is key. Even though there is a public database for vulnerability fixes the majority of them remain undisclosed to the public, therefore we propose a Machine Learning algorithm using NLP to detect security patches in Java Open Source Software. To train the model we preprocessed and extract patches from the commits present in two databases provided by Debricked and a public one released by Ponta et al. [57]. Two experiments were conducted, one performing binary classification and the other trying to have higher granularity classifying the macro-type of vulnerability. The proposed models leverage the structure of the input to have a better patch representation and they are based on RNNs, Transformers and CodeBERT [22], with the best performing model being the Transformer that surprisingly outperformed CodeBERT. The results show that it is possible to classify security patches but using more relevant pre-training techniques or tree-based representation of the code might improve the performance. / Användningen av programvara med öppen källkod blir alltmer populär, men det innebär en risk för att sårbarheter importeras från privata kodbaser. Säkerhetspatchar, som åtgärdar upptäckta sårbarheter, är viktiga för att skydda sig mot cyberattacker, och därför är det viktigt att kunna tillämpa alla säkerhetspatchar så snart de släpps. Även om det finns en offentlig databas för korrigeringar av sårbarheter förblir de flesta hemliga för allmänheten. Vi föreslår därför en maskininlärningsalgoritm som med hjälp av NLP upptäcker säkerhetspatchar i Java Open Source Software. För att träna modellen har vi förbehandlat och extraherat patchar från de commits som finns i två databaser, ena som tillhandahålls av Debricked och en annan offentlig databas som släppts av Ponta et al. [57]. Två experiment genomfördes, varav ett utförde binär klassificering och det andra försökte få en högre granularitet genom att klassificera makro-typen av sårbarheten. De föreslagna modellerna utnyttjar strukturen i indatat för att få en bättre representation av patcharna och de är baserade på RNNs, Transformers och CodeBERT [22], där den bäst presterande modellen var Transformer som överraskande nog överträffade CodeBERT. Resultaten visar att det är möjligt att klassificera säkerhetspatchar, men genom att använda mer relevanta förträningstekniker eller trädbaserade representationer av koden kan prestandan förbättras.