We present a novel robust hashing mechanism for models. Robust hashing algorithms (i.e. hashing algorithms that generate similar outputs from similar input data) are useful as a key building block in intellectual property protection, authenticity assessment and fast comparison and retrieval solutions
Model-driven development has become a leading paradigm for developing CPS because it enables the developer to verify safety requirements in early development phases and refine the models into an implementation preserving the verified requirements.
Second edition of our workshop exploring the mutual benefits of combining model-driven engineering and security techniques.
An initial roadmap towards the holistic protection of intellectual property (IP) in collaborative modeling scenarios based on the adaptation of Cryptography, Access-control and Digital Rights Management mechanisms
Read about our access-control mechanisms for models. We rely on a new domain-specific language tailored to the definition of RBAC rules on models and on its enforcement thanks to the automatic generation of security compliant (virtual) views.
A common problem when modeling software systems is the lack of support to specify how to enforce privacy concerns in data models. In this post, we propose a profile to define and enforce privacy concerns in UML class diagrams. Models annotated with our profile can be used in model-driven methodologies to generate privacy-aware applications.