Research Areas

The group develops and refines theories for foundational ontologies, which provide the most general and abstract categories necessary to describe and analyze any domain. These ontologies aim to capture the basic building blocks of reality, offering a structured framework that supports consistent and coherent conceptual models. The work on foundational ontologies contribute to the improvement of the Unified Foundational Ontology (UFO) and its derived ontology modeling language OntoUML.

The work on core ontologies focuses on developing and refining mid-level ontologies that bridge the gap between more abstract foundational ontologies and specialized domain ontologies. This research line aims to create reusable, domain-neutral concepts that can be applied across various fields, promoting interoperability and semantic integration among diverse systems. By providing structured frameworks that capture commonalities across different domains, the group enables more efficient development of domain-specific ontologies and facilitates communication and data exchange in complex, multi-domain environments. Examples of such core ontologies developed by the group include: risk, value, legal relations, money and resilience.

Leveraging foundational ontologies, the group explores ontology-driven approaches to conceptual modeling. This involves using ontological theories to guide the design and implementation of models that accurately represent the semantics of complex systems and real-world domains.

The research group applies their theoretical insights to create semantic artifacts—such as data models, taxonomies, and ontologies—that are directly applicable in various real-world domains, including healthcare, engineering, business, and information systems. These artifacts help improve data interoperability, information retrieval, and decision-making processes.

Traditional security solutions are targeted towards the protection from known threats and are dominantly based on insights acquired through costly manual analysis, which is often too slow to cope with the rapid emergence of new threats. To overcome this, we aim at a fully automated threat identification, analysis, and response and research the use of both semantic models and artificial intelligence to automatically analyze known threats with corresponding mitigation strategies and to learn prediction models that allow for the identification of new/unseen threats and adapted mitigation approaches. Moreover, we research automated security analysis techniques, such as static/dynamic analysis, symbolic execution, and fuzzing to test system and software components and discover, analyze, and patch new vulnerabilities. 

While traditional encryption technology can be used for the protection of data at rest and in transit, it requires a decryption step for processing the data, which in turn exposes the data in the clear and makes it vulnerable to attacks. We investigate the construction of cryptographic protocols based on non-traditional encryption, such as homomorphic encryption, that allow for the processing of data under encryption without the need to decrypt. Growing amounts of data and increasing complexities of the processing algorithms are complicating factors that largely lead to efficiency problems. We approach this by sacrificing some security for efficiency. By studying the success of possible leakage-abuse attacks, we can quantify the loss in security and achieve practical tradeoffs between security and efficiency. Lastly, to effectively protect against data breaches, we study decentralized access control approaches based on attribute-based encryption and distributed ledger technologies.

The group explores foundational theories and principles that guide the creation of effective and user-centered services. The research involves developing models and strategies for designing services that are scalable, adaptable, and aligned with user needs and business objectives.

The research on services leverages MDE to facilitate the design and implementation of service-oriented systems. By using high-level models to drive the development process, we aim to improve the consistency, maintainability, and interoperability of services across different platforms and technologies.

The group investigates the application of service-oriented architecture and design to pervasive/ubiquitous computing and IoT environments, focusing on the seamless integration of services into everyday life. The research addresses challenges related to context-awareness, adaptability, interoperability and the efficient delivery of services in dynamic, distributed environments.