MeGARA: Menu-based Game Abstraction and Abstraction Refinement of Markov Automata

Markov automata combine continuous time, probabilistic transitions, and nondeterminism in a single model. They represent an important and powerful way to model a wide range of complex real-life systems. However, such models tend to be large and difficult to handle, making abstraction and abstraction refinement necessary. In this paper we present an abstraction and abstraction refinement technique for Markov automata, based on the game-based and menu-based abstraction of probabilistic automata. First experiments show that a significant reduction in size is possible using abstraction.Comment: In Proceedings QAPL 2014, arXiv:1406.156

Possibilistic Information Flow Control for Workflow Management Systems

In workflows and business processes, there are often security requirements on both the data, i.e. confidentiality and integrity, and the process, e.g. separation of duty. Graphical notations exist for specifying both workflows and associated security requirements. We present an approach for formally verifying that a workflow satisfies such security requirements. For this purpose, we define the semantics of a workflow as a state-event system and formalise security properties in a trace-based way, i.e. on an abstract level without depending on details of enforcement mechanisms such as Role-Based Access Control (RBAC). This formal model then allows us to build upon well-known verification techniques for information flow control. We describe how a compositional verification methodology for possibilistic information flow can be adapted to verify that a specification of a distributed workflow management system satisfies security requirements on both data and processes.Comment: In Proceedings GraMSec 2014, arXiv:1404.163

Reconciling a component and process view

In many cases we need to represent on the same abstraction level not only system components but also processes within the system, and if for both representation different frameworks are used, the system model becomes hard to read and to understand. We suggest a solution how to cover this gap and to reconcile component and process views on system representation: a formal framework that gives the advantage of solving design problems for large-scale component systems.Comment: Preprint, 7th International Workshop on Modeling in Software Engineering (MiSE) at ICSE 201