1,102 research outputs found
Towards the Model-Driven Engineering of Secure yet Safe Embedded Systems
We introduce SysML-Sec, a SysML-based Model-Driven Engineering environment
aimed at fostering the collaboration between system designers and security
experts at all methodological stages of the development of an embedded system.
A central issue in the design of an embedded system is the definition of the
hardware/software partitioning of the architecture of the system, which should
take place as early as possible. SysML-Sec aims to extend the relevance of this
analysis through the integration of security requirements and threats. In
particular, we propose an agile methodology whose aim is to assess early on the
impact of the security requirements and of the security mechanisms designed to
satisfy them over the safety of the system. Security concerns are captured in a
component-centric manner through existing SysML diagrams with only minimal
extensions. After the requirements captured are derived into security and
cryptographic mechanisms, security properties can be formally verified over
this design. To perform the latter, model transformation techniques are
implemented in the SysML-Sec toolchain in order to derive a ProVerif
specification from the SysML models. An automotive firmware flashing procedure
serves as a guiding example throughout our presentation.Comment: In Proceedings GraMSec 2014, arXiv:1404.163
Model the System from Adversary Viewpoint: Threats Identification and Modeling
Security attacks are hard to understand, often expressed with unfriendly and
limited details, making it difficult for security experts and for security
analysts to create intelligible security specifications. For instance, to
explain Why (attack objective), What (i.e., system assets, goals, etc.), and
How (attack method), adversary achieved his attack goals. We introduce in this
paper a security attack meta-model for our SysML-Sec framework, developed to
improve the threat identification and modeling through the explicit
representation of security concerns with knowledge representation techniques.
Our proposed meta-model enables the specification of these concerns through
ontological concepts which define the semantics of the security artifacts and
introduced using SysML-Sec diagrams. This meta-model also enables representing
the relationships that tie several such concepts together. This representation
is then used for reasoning about the knowledge introduced by system designers
as well as security experts through the graphical environment of the SysML-Sec
framework.Comment: In Proceedings AIDP 2014, arXiv:1410.322
A Product Line Systems Engineering Process for Variability Identification and Reduction
Software Product Line Engineering has attracted attention in the last two
decades due to its promising capabilities to reduce costs and time to market
through reuse of requirements and components. In practice, developing system
level product lines in a large-scale company is not an easy task as there may
be thousands of variants and multiple disciplines involved. The manual reuse of
legacy system models at domain engineering to build reusable system libraries
and configurations of variants to derive target products can be infeasible. To
tackle this challenge, a Product Line Systems Engineering process is proposed.
Specifically, the process extends research in the System Orthogonal Variability
Model to support hierarchical variability modeling with formal definitions;
utilizes Systems Engineering concepts and legacy system models to build the
hierarchy for the variability model and to identify essential relations between
variants; and finally, analyzes the identified relations to reduce the number
of variation points. The process, which is automated by computational
algorithms, is demonstrated through an illustrative example on generalized
Rolls-Royce aircraft engine control systems. To evaluate the effectiveness of
the process in the reduction of variation points, it is further applied to case
studies in different engineering domains at different levels of complexity.
Subject to system model availability, reduction of 14% to 40% in the number of
variation points are demonstrated in the case studies.Comment: 12 pages, 6 figures, 2 tables; submitted to the IEEE Systems Journal
on 3rd June 201
AADLib, A Library of Reusable AADL Models
The SAE Architecture Analysis and Design Language is now a well-established language for the description of critical embedded systems, but also cyber-physical ones. A wide range of analysis tools is already available, either as part of the OSATE tool chain, or separate ones.
A key missing elements of AADL is a set of reusable building blocks to help learning AADL concepts, but also experiment already existing tool chains on validated real-life examples.
In this paper, we present AADLib, a library of reusable model elements. AADLib is build on two pillars: 1/ a set of ready-to- use examples so that practitioners can learn more about the AADL language itself, but also experiment with existing tools. Each example comes with a full description of available analysis and expected results. This helps reducing the learning curve of the language. 2/ a set of reusable model elements that cover typical building blocks of critical systems: processors, networks, devices with a high level of fidelity so that the cost to start a new project is reduced.
AADLib is distributed under a Free/Open Source License to further disseminate the AADL language. As such, AADLib provides a convenient way to discover AADL concepts and tool chains, and learn about its features
Model-based dependability analysis : state-of-the-art, challenges and future outlook
Abstract: Over the past two decades, the study of model-based dependability analysis has gathered significant research interest. Different approaches have been developed to automate and address various limitations of classical dependability techniques to contend with the increasing complexity and challenges of modern safety-critical system. Two leading paradigms have emerged, one which constructs predictive system failure models from component failure models compositionally using the topology of the system. The other utilizes design models - typically state automata - to explore system behaviour through fault injection. This paper reviews a number of prominent techniques under these two paradigms, and provides an insight into their working mechanism, applicability, strengths and challenges, as well as recent developments within these fields. We also discuss the emerging trends on integrated approaches and advanced analysis capabilities. Lastly, we outline the future outlook for model-based dependability analysis
Semantics of trace relations in requirements models for consistency checking and inferencing
Requirements traceability is the ability to relate requirements back to stakeholders and forward to corresponding design artifacts, code, and test cases. Although considerable research has been devoted to relating requirements in both forward and backward directions, less attention has been paid to relating requirements with other requirements. Relations between requirements influence a number of activities during software development such as consistency checking and change management. In most approaches and tools, there is a lack of precise definition of requirements relations. In this respect, deficient results may be produced. In this paper, we aim at formal definitions of the relation types in order to enable reasoning about requirements relations. We give a requirements metamodel with commonly used relation types. The semantics of the relations is provided with a formalization in first-order logic. We use the formalization for consistency checking of relations and for inferring new relations. A tool has been built to support both reasoning activities. We illustrate our approach in an example which shows that the formal semantics of relation types enables new relations to be inferred and contradicting relations in requirements documents to be determined. The application of requirements reasoning based on formal semantics resolves many of the deficiencies observed in other approaches. Our tool supports better understanding of dependencies between requirements
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