Towards Secure and Leak-Free Workflows Using Microservice Isolation

Data leaks and breaches are on the rise. They result in huge losses of money for businesses like the movie industry, as well as a loss of user privacy for businesses dealing with user data like the pharmaceutical industry. Preventing data exposures is challenging, because the causes for such events are various, ranging from hacking to misconfigured databases. Alongside the surge in data exposures, the recent rise of microservices as a paradigm brings the need to not only secure traffic at the border of the network, but also internally, pressing the adoption of new security models such as zero-trust to secure business processes. Business processes can be modeled as workflows, where the owner of the data at risk interacts with contractors to realize a sequence of tasks on this data. In this paper, we show how those workflows can be enforced while preventing data exposure. Following the principles of zero-trust, we develop an infrastructure using the isolation provided by a microservice architecture, to enforce owner policy. We show that our infrastructure is resilient to the set of attacks considered in our security model. We implement a simple, yet realistic, workflow with our infrastructure in a publicly available proof of concept. We then verify that the specified policy is correctly enforced by testing the deployment for policy violations, and estimate the overhead cost of authorization

KnetMiner - An integrated data platform for gene mining and biological knowledge discovery

Hassani-Pak K. KnetMiner - An integrated data platform for gene mining and biological knowledge discovery. Bielefeld: Universität Bielefeld; 2017.Discovery of novel genes that control important phenotypes and diseases is one of the key challenges in biological sciences. Now, in the post-genomics era, scientists have access to a vast range of genomes, genotypes, phenotypes and ‘omics data which - when used systematically - can help to gain new insights and make faster discoveries. However, the volume and diversity of such un-integrated data is often seen as a burden that only those with specialist bioinformatics skills, but often only minimal specialist biological knowledge, can penetrate. Therefore, new tools are required to allow researchers to connect, explore and compare large-scale datasets to identify the genes and pathways that control important phenotypes and diseases in plants, animals and humans. KnetMiner, with a silent "K" and standing for Knowledge Network Miner, is a suite of open-source software tools for integrating and visualising large biological datasets. The software mines the myriad databases that describe an organism’s biology to present links between relevant pieces of information, such as genes, biological pathways, phenotypes and publications with the aim to provide leads for scientists who are investigating the molecular basis for a particular trait. The KnetMiner approach is based on 1) integration of heterogeneous, complex and interconnected biological information into a knowledge graph; 2) text-mining to enrich the knowledge graph with novel relations extracted from literature; 3) graph queries of varying depths to find paths between genes and evidence nodes; 4) evidence-based gene rank algorithm that combines graph and information theory; 5) fast search and interactive knowledge visualisation techniques. Overall, [KnetMiner](http://knetminer.rothamsted.ac.uk) is a publicly available resource that helps scientists trawl diverse biological databases for clues to design better crop varieties and understand diseases. The key strength of KnetMiner is to include the end user into the “interactive” knowledge discovery process with the goal of supporting human intelligence with machine intelligence

Business process documentation in creative work systems:a design science study in television production

Die vorliegende Arbeit untersucht den Einfluss von Kreativität auf die Modellierung und Dokumentation von Geschäftsprozessen. Dabei wird ausgehend von einer theoretischen Basis eine Methode entwickelt, die die Erfassung kreativitätsintensiver Prozesse ermöglicht. Deren Besonderheit ist, dass sie das in der Prozessmodellierung vorherrschende strenge Kontrollflussparadigma aufbricht, um so dem Anspruch kreativer Arbeitssysteme an Flexibilität gerecht zu werden. Ausgehend vom kreativen Produkt werden dabei sukzessiv kreative Teilprozesse von administrativen Aufgaben isoliert, um so ein angemessenes Management beider zu ermöglichen. Die Methode wird in einer umfassenden Studie im Kontext der Fernsehproduktion in Deutschland evaluiert. Auf Basis semi-strukturierter Interviews werden dabei umfassende Modelle für die Produktlinien TV-Film, Serie, Daily Soap und Entertainment diskutiert. Die Ergebnisse werden abschließend auf die Methode und die zu Grunde liegende Theorie zurückgespiegelt.This study investigates the influence of creativity on the modeling and documentation of business processes. Based on a substantive theory a modeling method is developed that allows for the capturing of creativity-intensive processes. This method discards a strict and formal interpretation of the predominant control-flow paradigm in process modeling and thus conforms to the flexibility requirements of creative work systems. Emanating from the creative product, creative and administrative subprocesses are successively revealed, thus enabling the adequate management of both process types. The method is applied to the context of German television production. Comprising process models for the product lines television movie, primetime series, daily soap and entertainment are derived from qualitative interview data. The results of this evaluation are fed back to both the method as well as the foundational theory