8,396 research outputs found
Practical applications of probabilistic model checking to communication protocols
Probabilistic model checking is a formal verification technique for the analysis of systems that exhibit stochastic behaviour. It has been successfully employed in an extremely wide array of application domains including, for example, communication and multimedia protocols, security and power management. In this chapter we focus on the applicability of these techniques to the analysis of communication protocols. An analysis of the performance of such systems must successfully incorporate several crucial aspects, including concurrency between multiple components, real-time constraints and randomisation. Probabilistic model checking, in particular using probabilistic timed automata, is well suited to such an analysis. We provide an overview of this area, with emphasis on an industrially relevant case study: the IEEE 802.3 (CSMA/CD) protocol. We also discuss two contrasting approaches to the implementation of probabilistic model checking, namely those based on numerical computation and those based on discrete-event simulation. Using results from the two tools PRISM and APMC, we summarise the advantages, disadvantages and trade-offs associated with these techniques
On Synchronous and Asynchronous Monitor Instrumentation for Actor-based systems
We study the impact of synchronous and asynchronous monitoring
instrumentation on runtime overheads in the context of a runtime verification
framework for actor-based systems. We show that, in such a context,
asynchronous monitoring incurs substantially lower overhead costs. We also show
how, for certain properties that require synchronous monitoring, a hybrid
approach can be used that ensures timely violation detections for the important
events while, at the same time, incurring lower overhead costs that are closer
to those of an asynchronous instrumentation.Comment: In Proceedings FOCLASA 2014, arXiv:1502.0315
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The effect of multiple knowledge sources on learning and teaching
Current paradigms for machine-based learning and teaching tend to perform their task in isolation from a rich context of existing knowledge. In contrast, the research project presented here takes the view that bringing multiple sources of knowledge to bear is of central importance to learning in complex domains. As a consequence teaching must both take advantage of and beware of interactions between new and existing knowledge. The central process which connects learning to its context is reasoning by analogy, a primary concern of this research. In teaching, the connection is provided by the explicit use of a learning model to reason about the choice of teaching actions. In this learning paradigm, new concepts are incrementally refined and integrated into a body of expertise, rather than being evaluated against a static notion of correctness. The domain chosen for this experimentation is that of learning to solve "algebra story problems." A model of acquiring problem solving skills in this domain is described, including: representational structures for background knowledge, a problem solving architecture, learning mechanisms, and the role of analogies in applying existing problem solving abilities to novel problems. Examples of learning are given for representative instances of algebra story problems. After relating our views to the psychological literature, we outline the design of a teaching system. Finally, we insist on the interdependence of learning and teaching and on the synergistic effects of conducting both research efforts in parallel
Formal Analysis of V2X Revocation Protocols
Research on vehicular networking (V2X) security has produced a range of
security mechanisms and protocols tailored for this domain, addressing both
security and privacy. Typically, the security analysis of these proposals has
largely been informal. However, formal analysis can be used to expose flaws and
ultimately provide a higher level of assurance in the protocols.
This paper focusses on the formal analysis of a particular element of
security mechanisms for V2X found in many proposals: the revocation of
malicious or misbehaving vehicles from the V2X system by invalidating their
credentials. This revocation needs to be performed in an unlinkable way for
vehicle privacy even in the context of vehicles regularly changing their
pseudonyms. The REWIRE scheme by Forster et al. and its subschemes BASIC and
RTOKEN aim to solve this challenge by means of cryptographic solutions and
trusted hardware.
Formal analysis using the TAMARIN prover identifies two flaws with some of
the functional correctness and authentication properties in these schemes. We
then propose Obscure Token (OTOKEN), an extension of REWIRE to enable
revocation in a privacy preserving manner. Our approach addresses the
functional and authentication properties by introducing an additional key-pair,
which offers a stronger and verifiable guarantee of successful revocation of
vehicles without resolving the long-term identity. Moreover OTOKEN is the first
V2X revocation protocol to be co-designed with a formal model.Comment: 16 pages, 4 figure
Incremental verification and synthesis of discrete-event systems guided by counter-examples
This article presents new approaches to system verification and synthesis based on subsystem verification and the novel combined use of counterexamples and heuristics to identify suitable subsystems incrementally. The scope of safety properties considered is limited to behavioral inclusion and controllability. The verification examples considered provide a comparison of the approaches presented with straightforward state exploration and an understanding of their applicability in an industrial context
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