Nathalie Aussenac-Gilles

With the emergence of the digital transition, the need to control the processing of digital information has significantly increased. In the EU in particular, Law Enforcement Agencies (LEAs) are caused to exchange information. In recent years, many regulations have emerged to control data processing and exchange. Texts other than the GDPR, such as the “Law Enforcement Directive (LED)”, appeared to regulate specifically their data processing. And although many new formalisms have emerged to represent legal norms and rules, few are provided with a reasoning mechanism. The explainability of the results of systems using these formalisms also remains a major issue when dealing with critical decision situations. This paper aims to propose a framework to operate formal rules from regulations and guide a user in its decision process in a situation of data processing by LEAs by focusing on both the operability of the rules through reasoning and the explainability of the results from the reasoning.

Purpose: The first objective of this research is to represent an event with 5W1H characteristics (who, what, where, when, why, and how) through ontologies. The second objective is to propose an approach for enriching an event knowledge graph (EKG) based on this ontology using EvCBR, an outperforming case-based reasoning algorithm found in the literature. Furthermore, we have studied the impact of each W (Who, Where, and When) on the performance of EvCBR on the Wikipedia Causal Event dataset. Methodology: We proposed the XPEventCore ontology to represent 5W1H characteristics of events by integrating multiple event ontologies (SEM and FARO) and introduced new object properties for representing Cause and Method to answer “Why” and “How” questions. We adopted this XPEventCore ontology for a specific use case (the MR4AP Wikipedia dataset), and populated the EKG. Furthermore, we adapted EvCBR, a case-based reasoning approach, to enrich this EKG. Findings: XPEventCore ontology provides a structured and adaptable foundation for capturing the essential facets of an event. It can be adapted to any domain (like MR4AP Wikipedia dataset) and populated to generate EKGs. Then, we applied EvCBR, and subsequent analysis revealed that reasoning had a significant impact. Notably, EvCBR outperformed with reasoning approaches on the dataset. Originality: XPEventCore ontology is the first ontology that represents an event with 5W1H characteristics.

Access-control systems are key components to guarantee the security and confidentiality of resource repositories. Most access-control systems that are today de facto standards were designed before the gen-eralization of cloud services and Internet of Things. Such systems are particularly heavy to maintain in today’s context, which gave rise to more flexible approaches based on logical description using semantic web technologies. In this paper, we propose a survey of these semantic ap-proaches. Although this survey does not aim at being exhaustive, it offers the reader an overview of the main trends and their limitations.