Digitalization brings many new opportunities for businesses and governments by fostering the development of innovative online services. However, this development also brings new challenges, notably in terms of intelligence, interoperability, security, and privacy. Therefore, research in this context aims to realize the vision of meaningful computing within trusted digital environments by advancing the forefront of semantic modeling, enhancing cybersecurity, and innovating service design.
In this track, we aim at conducting projects focussing on:
Methods and techniques for ontology-driven conceptual modeling, FAIR data stewardship, requirements conceptualization, architecture design, and model-driven engineering of service systems.
Foundational, core, domain, service, and application ontologies and service composition frameworks to realize semantic interoperability and meaningful enterprise services.
Automated methodologies for analyzing systems to identify and mitigate security flaws and to detect and assess potential threats.
Algorithms and protocols that provably secure the underlying IT infrastructure and that can thwart or detect attacks.
Data-driven services that can make sense of their context and can reliably and timely react to changing situations.
Privacy-enhancing technologies and design data protection and anonymization techniques for services that collect and process sensitive data.
The topics that are currently available can be found below. (Note: The list will change in the coming days when extra topics become available.)
Automated extraction of defanged Indicators of Compromise from cyber threat intelligence reports.
Gamification on Steganography
Modelling and analyzing sustainability of business ecosystems.
Qualitative and quantitative evaluation of the value of digital data sharing in business collaborations.
Federating data spaces to support efficient and secure business collaboration in the digital domain.
Metrics and methods for evaluating semantic and organizational interoperability.
Towards Digital Twin: 3D environment for rover simulation.
Raspberry Pi OS Emulator for Smart Industry Digital Lab.
Microservices architecture using the OpenTripModel and EDIFACT for logistics.
Microservices NF requirements: resiliency, scalability, performance and security.
Personal Health Train for data federation.
Ontology for education improvement of the BIT programme.
Continuous Model-Based System Engineering of Smart Products.
Integration of Application Lifecycle Management (ALM) with Product Lifecycle Management (PLM) for Smart Applications.
Integration of drone data with Laboratory Information Management System.
Data integration of autonomous vehicles.
Smart application interoperability with ETSI SAREF and/or HL7 FHIR standards, such as a smart health app that uses ECG Consensys Shimmer3 device..
Interoperable drone system for building inspection.
Measuring the energy consumption/carbon footprint of encrypted ML inference
Measuring the energy consumption/carbon footprint of HTTPS Web browsing
Measuring the energy consumption/carbon footprint of encrypted databases (MongoDB)
Measuring the energy consumption/carbon footprint of differentially private ML
AI-based verbalisation design and implementation of data access and data request policies using ODRL
Evaluation of visualisation alternatives for RDF-based metadata schemas (Web form and graph diagram)
Design and analysis of federated analysis interactions between data providers and consumers (FAIR Data Train)
Implementing a decision tree for aligning domain ontologies to gUFO
Cognitive psychology meets data modeling: An empirical study on natural categories
Risk and Security Modeling in ArchiMate: A Case Study
Discrete Event Simulations in ArchiMate
Well-Founded Knowledge Graph Creation for Risk Management
Design RESTfull APIs from ontologies with OntoUML and OpenAPI
Validating the COMET-A ontology for competency-based education
Collecting Virtual Escaping Attacks for Reproducibility and Dataset Creation
If you are interested in another topic related to the academic staff, research areas, running projects, or any other questions related to the track, please contact Tiago Prince Sales.
Students should choose a topic, contact the supervisor, and get approval to work on the topic.
Before November 11 2024, send the track chair your topic's title and supervisor's name.