PhD Students
Ongoing PhDs :
- Cyberbullying Detection, Fatemeh ANSARI, industrial funding.
- Privacy protection in IoT, Karam Bou Chaya, industrial funding.
Completed PhDs:
- A Formal Framework for Process Interoperability in Dynamic Collaboration Environments, Malik KHALFALLAH, industrial funding, 2015.
- Service composition in uncertain environments, Soumaya AMDOUNI, 2015.
- Contributions to configurable business process management, Wehbi BENALLAL, industrial funding, 2019.
- Data service composition with uncertain semantics, Abdelhamid MALKI, 2016.
Research Topics
Privacy Engineering in IoT Applications and Environments
The objective of this research work is to empower the users of IoT-based cyber physical systems to protect their privacy by themselves. Our research aims to allow users to identify the privacy risks involved in sharing private data with a data consumer, assess the value of their private data based on identified risks and take a pragmatic data sharing decision balancing the risks with the benefits generated by the sharing.
Privacy Engineering in Service Oriented Architectures
This research builds on my research work on Web service composition during my PhD thesis. The objective of this work was to ensure data privacy in service oriented applications in the healthcare domain. We built a new privacy preserving composition execution system. Our system allows to execute queries over multiple data services without revealing any extra information to any of the involved services. None of involved services (and their providers) is able to infer any information about the data the other services provide beyond what is permitted.
Web Service Composition
In this research work we addressed the problem of data web service composition. We proposed a novel approach for querying and automatically composing data services. The proposed approach largely draws from the experiences and lessons learned in the areas of service composition, ontology, and answering queries over views. First, we introduced a model for the description of data web services and specification of service-oriented queries. We model data services as RDF views over a mediated (domain) ontology. Each RDF view contains concepts and relations from the mediated ontology to capture the semantic relationships between input and output parameters. Second, we propose query rewriting algorithms for processing queries over data services. The query mediator automatically transforms a user’s query (during the query rewriting stage) into a composition of data services.
Social data analysis for cyber-security
We conducted this research work in the context of a European research project funded by the European Union. We proposed an approach to analyze social networks with the objective of identifying violent radicalized individuals. Our approach computes a set of radicalization indicators, defined by domain experts, to assess the radicalization level of a social network user.
Research Projects
Risk-Track (2016-8, Role: Research Team Leader): is a European project (Justice Program) whose objective is to build a data analysis tool for the identification of violent radicals and hate speech on social networks. Risk-Track involves the following partners: Universidad Autonoma de Madrid (Spain), Claude Bernard Lyon 1 University (France), the Parc Sanitari Sant Joan de Deu (Spain) and the Cyprus Neuroscience & Technology Institute (Cyprus).
Securing the Sky SecSKY (2017, Role: Co-PI): This project is funded by the CNRS. In this project, we propose a privacy-preserving data integration approach. The proposed approach allows us to integrate data about the same individual across independent data sources without allowing individual sources to infer information about the data held by each other. We applied our solution to the policing domain. Our solution allows police inspectors to identify terrorist suspects on flights by integrating data from several data sources such as police databases, flight passenger lists, banks and borders databases.
Privacy for Cyber Physical Systems (2015, Role: PI): This project is funded by the CNRS. In this project, we explored the privacy concerns raised by the use of smart cyber physical systems.
Adaptive Security and Privacy ASAP (2014-2016, Role: Member)
PAIRSE (2009-2013, Role: Member): The PAIRSE project aims at providing a flexible, loosely coupled and privacy-preserving data integration system in P2P environments. The project exploits recent Web standards and technologies such as Web services and ontologies to export data from autonomous data providers as reusable services, and proposes the use of service composition as a viable solution to answer data integration needs on the fly. The project proposed new composition algorithms and service/composition execution models that preserve privacy of data manipulated by services and compositions. The proposed integration system was demonstrated at EDBT 2013 and VLDB 2011.