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Diese Arbeit beschäftigt sich mit dem Thema NoSQL-Datenbanken in Webanwendungen. Dabei solle die verschiedenen Konzepte aktueller NoSQL-Datenbanken erläutert und exemplarische Implementierungen der einzelnen Konzepte vorgestellt werden. Anschließend wird der Einsatz in modernen Webanwendungen gezeigt. Hierzu soll eine einfache Social-Community-Plattform erstellt werden, welche zuerst auf Basis eines relationalen Datenbank Management System erstellt wird. Um die Einsatzmöglichkeiten der NoSQL-Vertreter zu zeigen werden anschließend einzelne Funktionen mit NoSQL-Datenbank implementiert und die Vor- und Nachteile erörtert.
Threat Modelling is an accepted technique to identify general threats as early as possible in the software development lifecycle. Previous work of ours did present an open-source framework and web-based tool (OVVL) for automating threat analysis on software architectures using STRIDE. However, one open problem is that available threat catalogues are either too general or proprietary with respect to a certain domain (e.g. .Net). Another problem is that a threat analyst should not only be presented (repeatedly) with a list of all possible threats, but already with some automated support for prioritizing these. This paper presents an approach to dynamically generate individual threat catalogues on basis of the established CWE as well as related CVE databases. Roughly 60% of this threat catalogue generation can be done by identifying and matching certain key values. To map the remaining 40% of our data (~50.000 CVE entries) we train a text classification model by using the already mapped 60% of our dataset to perform a supervised machine-learning based text classification. The generated entire dataset allows us to identify possible threats for each individual architectural element and automatically provide an initial prioritization. Our dataset as well as a supporting Jupyter notebook are openly available.