Abstract. We introduce the problem of Model Repair for Probabilistic Systems as follows. Given a probabilistic system M and a probabilistic temporal logic formula φ such that M fails to satisfy φ, the Model Repair problem is to find an M that satisfies φ and differs from M only in the transition flows of those states in M that are deemed controllable. Moreover, the cost associated with modifying M 's transition flows to obtain M should be minimized. Using a new version of parametric probabilistic model checking, we show how the Model Repair problem can be reduced to a nonlinear optimization problem with a minimal-cost objective function, thereby yielding a solution technique. We demonstrate the practical utility of our approach by applying it to a number of significant case studies, including a DTMC reward model of the Zeroconf protocol for assigning IP addresses, and a CTMC model of the highly publicized Kaminsky DNS cache-poisoning attack.

The focus of this work is the on-demand resource provisioning in cloud computing, which is commonly referred to as cloud elasticity. Although a lot of effort has been invested in developing systems and mechanisms that enable elasticity, the elasticity decision policies tend to be designed without quantifying or guaranteeing the quality of their operation. We present an approach towards the development of more formalized and dependable elasticity policies. We make two distinct contributions. First, we propose an extensible approach to enforcing elasticity through the dynamic instantiation and online quantitative verification of Markov Decision Processes (MDP) using probabilistic model checking. Second, various concrete elasticity models and elasticity policies are studied. We evaluate the decision policies using traces from a real NoSQL database cluster under constantly evolving external load. We reason about the behaviour of different modeling and elasticity policy options and we show that our proposal can improve upon the state-of-the-art in significantly decreasing under-provisioning while avoiding over-provisioning.

In this case study, we apply the architecture-based design approach to the control software of the CubETH satellite. Architectures are a means for ensuring global coordination properties and thus, achieving correctness of complex systems by construction. We illustrate the following three steps of the design approach: 1) definition of a domain-specific taxonomy of architecture styles; 2) design of the software model by applying architectures to enforce the required properties; 3) deadlock-freedom analysis of the resulting model. We provide a taxonomy of architecture styles for satellite on-board software, formally defined by architecture diagrams in the BIP component-based framework. We show how architectures are instantiated from the diagrams and applied to a set of atomic components. Deadlock-freedom of the resulting model is verified using DFinder from the BIP tool-set. We provide additional validation of our approach by using the nuXmv model checker to verify that the properties enforced by the architectures are, indeed, satisfied by the model.

The early validation of requirements aims to reduce the need for the high-cost validation testing and corrective measures at late development stages. This work introduces a systematic process for the unambiguous specification of system requirements and the guided derivation of formal properties, which should be implied by the system 's structure and behavior in conjunction with its external stimuli. This rigorous design takes place through the incremental construction of a model using the BIP (Behavior-Interaction-Priorities) component framework. It allows building complex designs by composing simpler reusable designs enforcing given properties. If some properties are neither enforced nor verified, the model is refined or certain requirements are revised. A validated model provides evidence of requirements' consistency and design correctness. The process is semi-automated through a new tool and existing verification tools. Its effectiveness was evaluated on a set of requirements for the control software of the CubETH nanosatellite and an extract of software requirements for a Low Earth Orbit observation satellite. Our experience and obtained results helped in identifying open challenges for applying the method in industrial context. These challenges concern with the domain knowledge representation, the expressiveness of used specification languages, the library of reusable designs and scalability.

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The size and complexity of software in spacecraft is increasing exponentially, and this trend complicates its validation within the context of the overall spacecraft system. Current validation methods are labor-intensive as they rely on manual analysis, review and inspection. For future space missions, we developed -with challenging requirements from the European space industry -a novel modeling language and toolset for a (semi-)automated validation approach. Our modeling language is a dialect of AADL and enables engineers to express the system, the software, and their reliability aspects. The COMPASS toolset utilizes state-of-the-art model checking techniques, both qualitative and probabilistic, for the analysis of requirements related to functional correctness, safety, dependability and performance. Several pilot projects have been performed by industry, with two of them having focused on the system-level of a satellite platform in development. Our efforts resulted in a significant advancement of validating spacecraft designs from several perspectives, using a single integrated system model. The associated technology readiness level increased from level 1 (basic concepts and ideas) to early level 4 (laboratory-tested).

Abstract-We use the probabilistic model checker PRISM to formally model and analyze the highly publicized Kaminsky DNS cache-poisoning attack. DNS (Domain Name System) is an internet-wide, hierarchical naming system used to translate domain names such as google.com into physical IP addresses such as 208.77.188.166. The Kaminsky DNS attack is a recently discovered vulnerability in DNS that allows an intruder to hijack a domain; i.e. corrupt a DNS server so that it replies with the IP address of a malicious web server when asked to resolve URLs within a non-malicious domain such as google.com. A proposed fix for the attack is based on the idea of randomizing the source port a DNS server uses when issuing a query to another server in the DNS hierarchy.We use PRISM to introduce a Continuous Time Markov Chain representation of the Kaminsky attack and the proposed fix, and to perform the required probabilistic model checking. Our results, gleaned from more than 240 PRISM runs, formally validate the existence of the Kaminsky cache-poisoning attack even in the presence of an intruder with virtually no knowledge of the victim DNS server's actions. They also serve to quantify the effectiveness of the proposed fix: using nonlinear least-squares curve fitting, we show that the probability of a successful attack obeys a 1/N distribution, where N is the upper limit on the range of source-port ids. We also demonstrate an increasing attack probability with an increasing number of attempted attacks or increasing rate at which the intruder guesses the source-port id.

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