CAUTIS Bogdan
Ph.D
Group : Artificial Intelligence and Inference Systems

Signing and Reasoning about Tree Updates

Starts on
Advisor : ABITEBOUL, Serge

Funding :
Affiliation : INRIA
Laboratory :

Defended on 01/09/2005, committee :

Research activities :
   - XML

Abstract :
The purpose of this thesis is to address some of the security issues that are raised in distributed XML data management, with a focus on integrity in data exchange.

We first address the need to allow pre-defined modifications for sensitive exchanged data, by considering two models for expressing fine-grained updates restrictions on XML data, namely emph{+/- Annotated Trees} and emph{XML Update Constraints}. To enforce these models, we investigate cryptographic mechanisms by which some modifications may still occur, without causing the invalidation of the data. In order to support rich restrictions without disclosing the history of updates, we devise a first homomorphic digital signature scheme for emph{insert-only collections}.

As a direct application of homomorphic signatures, we then consider a setting in which parties exchange modifiable emph{queries}. More precisely, we take a first step towards enabling distributed access control, when policies and their enforcement are not handled by the actual data sources, being (partially) delegated to third-parties. Our approach relies on a flexible mechanism for signing queries, that allows their rewriting into authorized forms.

In a second part of this thesis, the focus shifts from integrity enforcement to reasoning about integrity properties and the dynamic nature of published or exchanged XML data. More precisely, we study implication problems for the emph{XML Update Constraints} formalism, that describes in terms of XPath queries how an XML document can evolve. Besides classical constraint implication, we study instance-based implication, with respect to a current tree instance, resulting from a series of unknown updates.

CAUSAL LEARNING FOR DIAGNOSTIC SUPPORT


CAUSAL UNCERTAINTY QUANTIFICATION UNDER PARTIAL KNOWLEDGE AND LOW DATA REGIMES


MICRO VISUALIZATIONS: DESIGN AND ANALYSIS OF VISUALIZATIONS FOR SMALL DISPLAY SPACES
The topic of this habilitation is the study of very small data visualizations, micro visualizations, in display contexts that can only dedicate minimal rendering space for data representations. For several years, together with my collaborators, I have been studying human perception, interaction, and analysis with micro visualizations in multiple contexts. In this document I bring together three of my research streams related to micro visualizations: data glyphs, where my joint research focused on studying the perception of small-multiple micro visualizations, word-scale visualizations, where my joint research focused on small visualizations embedded in text-documents, and small mobile data visualizations for smartwatches or fitness trackers. I consider these types of small visualizations together under the umbrella term ``micro visualizations.'' Micro visualizations are useful in multiple visualization contexts and I have been working towards a better understanding of the complexities involved in designing and using micro visualizations. Here, I define the term micro visualization, summarize my own and other past research and design guidelines and outline several design spaces for different types of micro visualizations based on some of the work I was involved in since my PhD.