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Paula Herber

Publications and source records attributed to Paula Herber.

2 recordsLinked to original sources

Automated Abstraction Refinement for Information Flow Security in Embedded Systems

Information flow analysis (IFA) is a powerful technique for verifying confidentiality and integrity and is therefore highly desirable for security-sensitive embedded systems. However, as these systems are inherently concurrent and time-dependent, existing IFA for embedded systems tend to be either imprecise or expensive. In this paper, we propose an approach to tackle this problem using automatic abstraction refinement. The key idea is to heuristically choose abstraction levels based on information about dependencies between states and detected potential information leakage. Our approach builds on previous work, where we leverage symbolic execution to precisely capture data, control, timing, and event dependencies between processes within an IFA. To capture values symbolically, this analysis uses abstract interpretation. While the existing approach requires manual definition of abstraction levels, our novel contribution in this paper is using carefully designed heuristics to select these levels automatically. The aim is to keep analysis times acceptable while also retaining enough information to decide whether or not illegal information flow is possible. We have implemented our approach for the system design language SystemC and demonstrate its feasibility with experimental results on several shared bus architectures.

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Modeling Uncertainty: From Simulink to Stochastic Hybrid Automata

Simulink is widely used in industrial design processes to model increasingly complex embedded control systems. Thus, their formal analysis is highly desirable. However, this comes with two major challenges: First, Simulink models often provide an idealized view of real-life systems and omit uncertainties such as, aging, sensor noise or failures. Second, the semantics of Simulink is only informally defined. In this paper, we present an approach to formally analyze safety and performance of embedded control systems modeled in Simulink in the presence of uncertainty. To achieve this, we 1) model different types of uncertainties as stochastic Simulink subsystems and 2) extend an existing formalization of the Simulink semantics based on stochastic hybrid automata (SHA) by providing transformation rules for the stochastic subsystems. Our approach gives us access to established quantitative analysis techniques, like statistical model checking and reachability analysis. We demonstrate the applicability of our approach by analyzing safety and performance in the presence of uncertainty for two smaller case studies.

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