Utilizing Remote Evaluation for Providing Data Sovereignty in Data-sharing Ecosystems

The maintenance of digital sovereignty is an important aspect of data-driven business models and data-sharing ecosystems. Considering this, sensitive data is often stored in proprietary systems under the data owner’s control and with appropriate security mechanisms. However, nowadays, it is often necessary to share data. As executing unknown and untrusted code on systems containing sensitive data is potentially dangerous, data-processing algorithms cannot be directly sent to the data-storing systems, as one solution. Instead, we have implemented an approach called remote processing that uses the domain-specific language \degree{}, which provides built-in usage control mechanisms for data processing tasks. The approach extends the well-known remote processing paradigm that allows controlled, distributed data usage without actual data sharing (transmission via network). Instead of classified data, applications and their execution results are transmitted. This way, sensitive data is never directly exposed to third parties. Furthermore, the application-integrated usage control mechanisms prevent malicious data usage

Treating the End of the Data Life Cycle as a First-Class Citizen in Data Engineering

Evolving regulatory frameworks, digital decarbonization, or new management challenges due to exponential data growth are bringing end-of-life data management to the forefront and making it an important building block in data engineering. However, the end of the data life cycle and in particular its management has received little attention in literature and practice. We argue this is partly due to the lack of an overarching model that creates a common understanding that data engineering experts and practitioners can build upon. We present Destroy Claims, which provides a standardized and comprehensive description of the end of the data life cycle and a corresponding architectural proposal for its integration. We demonstrate the feasibility of the solution through a use case inspired by practice, an evaluation gathered from expert discussions, and a survey. The results indicate that the proposed solution is a promising approach to support end-of-life data management in practice

Thoughts about using Constraint Solvers in Action

SMT solvers power many automated security analysis tools today. Nevertheless, a smooth integration of SMT solvers into programs is still a challenge that lead to different approaches for doing it the right way. In this paper, we review the state of the art for interacting with constraint solvers. Based on the different ideas found in literature we deduce requirements for a constraint solving service simplifying the integration challenge. We identify that for some of those ideas, it is required to run large scale experiments for evaluating some of the ideas behind the requirements empirically. We show that the platform is capable of running such an experiment for the case of measuring the impacts of seeds on the solver runtime

Initial CONNECT Architecture

Interoperability remains a fundamental challenge when connecting heterogeneous systems which encounter and spontaneously communicate with one another in pervasive computing environments. This challenge is exasperated by the highly heterogeneous technologies employed by each of the interacting parties, i.e., in terms of hardware, operating system, middleware protocols, and application protocols. The key aim of the CONNECT project is to drop this heterogeneity barrier and achieve universal interoperability. Here we report on the development of the overall CONNECT architecture that will underpin this solution; in this respect, we present the following contributions: i) an elicitation of interoperability requirements from a set of pervasive computing scenarios, ii) a survey of existing solutions to interoperability, iii) an initial view of the CONNECT architecture, and iv) a series of experiments to provide initial validation of the architecture

Formal Methods for a Digital Industry

The industrial track at ISoLA 2021 provided a platform for presenting industrial perspectives on digitalization and for discussing trends and challenges in the ongoing digital transformation from the perspective of where and how formal methods can contribute to addressing the related technical and societal challenges. The track continued two special tracks at ISoLA conferences focused on the application of learning techniques in software engineering and software products, and industrial applications of formal methods in the context of Industry 4.0. Topics of interest included but were not limited to Industry 4.0, industrial applications of formal methods and testing, as well as applications of machine learning in industrial contexts