Model-Based Security Testing

Security testing aims at validating software system requirements related to security properties like confidentiality, integrity, authentication, authorization, availability, and non-repudiation. Although security testing techniques are available for many years, there has been little approaches that allow for specification of test cases at a higher level of abstraction, for enabling guidance on test identification and specification as well as for automated test generation. Model-based security testing (MBST) is a relatively new field and especially dedicated to the systematic and efficient specification and documentation of security test objectives, security test cases and test suites, as well as to their automated or semi-automated generation. In particular, the combination of security modelling and test generation approaches is still a challenge in research and of high interest for industrial applications. MBST includes e.g. security functional testing, model-based fuzzing, risk- and threat-oriented testing, and the usage of security test patterns. This paper provides a survey on MBST techniques and the related models as well as samples of new methods and tools that are under development in the European ITEA2-project DIAMONDS.Comment: In Proceedings MBT 2012, arXiv:1202.582

TestML- A Test Exchange Language for Model-based Testing of Embedded Software

Abstract Test processes in the automotive industry are tool-intensive and affected by technologically heterogeneous test infrastructures. In the industrial practice a product has to pass tests at several levels of abstraction such as Model-in-the-Loop (MIL), Software-in-the-Loop (SIL) and Hardware-in-the-Loop (HIL) tests. Different test systems are applied for this purpose (e.g. dSPACE MTest, dSPACE Automation Desk, National Instruments Teststand) and almost each test system requests its own proprietary test description language. The exchange of tests between different test systems and the reuse of tests between different test levels is normally not possible. Efforts to integrate these heterogeneous test environments, to address test exchange in a general manner and to standardize and harmonize the existing language environment are still at the beginning and not tailored towards the requirements of the automotive domain. To keep the whole development and test process efficient and manageable, the definition of an integrated and seamless approach is required. TestML – the test exchange language we present in this article – is defined to overcome the technological obstacles (different test language syntax and semantics, different data formats and interface descriptions) that almost automatically accompany the application of heterogeneous test tools and test infrastructures. TestML supports the exchange of tests between different test notations in a heterogeneous tool environment. In this paper, we introduce the XML schema of TestML and demonstrate the efficiency of the interchange format by giving examples from the model-based development of electronic control units. Tool support is illustrated by an application with Simulink/Stateflow.

Screens in fly and beetle reveal vastly divergent gene sets required for developmental processes

Background: Most of the known genes required for developmental processes have been identified by genetic screens in a few well-studied model organisms, which have been considered representative of related species, and informative-to some degree-for human biology. The fruit fly Drosophila melanogaster is a prime model for insect genetics, and while conservation of many gene functions has been observed among bilaterian animals, a plethora of data show evolutionary divergence of gene function among more closely-related groups, such as within the insects. A quantification of conservation versus divergence of gene functions has been missing, without which it is unclear how representative data from model systems actually are. Results: Here, we systematically compare the gene sets required for a number of homologous but divergent developmental processes between fly and beetle in order to quantify the difference of the gene sets. To that end, we expanded our RNAi screen in the red flour beetle Tribolium castaneum to cover more than half of the protein-coding genes. Then we compared the gene sets required for four different developmental processes between beetle and fly. We found that around 50% of the gene functions were identified in the screens of both species while for the rest, phenotypes were revealed only in fly (similar to 10%) or beetle (similar to 40%) reflecting both technical and biological differences. Accordingly, we were able to annotate novel developmental GO terms for 96 genes studied in this work. With this work, we publish the final dataset for the pupal injection screen of the iBeetle screen reaching a coverage of 87% (13,020 genes). Conclusions: We conclude that the gene sets required for a homologous process diverge more than widely believed. Hence, the insights gained in flies may be less representative for insects or protostomes than previously thought, and work in complementary model systems is required to gain a comprehensive picture. The RNAi screening resources developed in this project, the expanding transgenic toolkit, and our large-scale functional data make T. castaneum an excellent model system in that endeavor

Large scale RNAi screen in Tribolium reveals novel target genes for pest control and the proteasome as prime target

Background: Insect pest control is challenged by insecticide resistance and negative impact on ecology and health. One promising pest specific alternative is the generation of transgenic plants, which express double stranded RNAs targeting essential genes of a pest species. Upon feeding, the dsRNA induces gene silencing in the pest resulting in its death. However, the identification of efficient RNAi target genes remains a major challenge as genomic tools and breeding capacity is limited in most pest insects impeding whole-animal-high-throughput-screening. Results: We use the red flour beetle Tribolium castaneum as a screening platform in order to identify the most efficient RNAi target genes. From about 5,000 randomly screened genes of the iBeetle RNAi screen we identify 11 novel and highly efficient RNAi targets. Our data allowed us to determine GO term combinations that are predictive for efficient RNAi target genes with proteasomal genes being most predictive. Finally, we show that RNAi target genes do not appear to act synergistically and that protein sequence conservation does not correlate with the number of potential off target sites. Conclusions: Our results will aid the identification of RNAi target genes in many pest species by providing a manageable number of excellent candidate genes to be tested and the proteasome as prime target. Further, the identified GO term combinations will help to identify efficient target genes from organ specific transcriptomes. Our off target analysis is relevant for the sequence selection used in transgenic plants