Differential Privacy for Relational Algebra: Improving the Sensitivity Bounds via Constraint Systems

Differential privacy is a modern approach in privacy-preserving data analysis to control the amount of information that can be inferred about an individual by querying a database. The most common techniques are based on the introduction of probabilistic noise, often defined as a Laplacian parametric on the sensitivity of the query. In order to maximize the utility of the query, it is crucial to estimate the sensitivity as precisely as possible. In this paper we consider relational algebra, the classical language for queries in relational databases, and we propose a method for computing a bound on the sensitivity of queries in an intuitive and compositional way. We use constraint-based techniques to accumulate the information on the possible values for attributes provided by the various components of the query, thus making it possible to compute tight bounds on the sensitivity.Comment: In Proceedings QAPL 2012, arXiv:1207.055

Derived classes as a basis for views in UML/OCL data models

UML is the de facto standard language for analysis and design in object-oriented frameworks. Information systems, and in particular information systems based on databases and their applications, rely heavily on sound principles of analysis and design. Many present-day database applications employ object-oriented principles in the phases of analysis and design due to the advantages of expressiveness and clarity of such languages as UML. Database specifications often involve specifications of constraints, and the Object Constraint Language (OCL) - as part of UML - can aid in the unambiguous modelling of database constraints. One of the central notions in database modelling and in constraint specifications is the notion of a database view. A database view closely corresponds to the notion of derived class in UML. This paper will show how the notion of a derived class in UML can be given a precise semantics in terms of OCL. We will then demonstrate that the notion of a relational database view can be correctly expressed as a derived class in UML/OCL. A central part of our investigation concerns the generality of our manner of representing relational views in OCL. An important problem that we address in this respect is the representation of product spaces and relational joins. Joins are often essential in view definitions, and we shall demonstrate how we can express Cartesian products and joins within the current framework of UML/OCL language by employing the notions of derived class. As a consequence, OCL will be shown to be equipped with the full expressive power of the relational algebra, offering support for the claim that OCL can be useful as a general query language within the framework of the UML/OCL data model.

Groupoids, Frobenius algebras and Poisson sigma models

In this paper we discuss some connections between groupoids and Frobenius algebras specialized in the case of Poisson sigma models with boundary. We prove a correspondence between groupoids in the category Set and relative Frobenius algebras in the category Rel, as well as an adjunction between a special type of semigroupoids and relative H*-algebras. The connection between groupoids and Frobenius algebras is made explicit by introducing what we called weak monoids and relational symplectic groupoids, in the context of Poisson sigma models with boundary and in particular, describing such structures in the ex- tended symplectic category and the category of Hilbert spaces. This is part of a joint work with Alberto Cattaneo and Chris Heunen.Comment: 12 pages, 1 figure. To appear in "Mathematical Aspects of Quantum Field Theories". Mathematical Physical Studies, Springer. Proceedings of the Winter School in Mathematical Physics, Les Houges, 201