Fingerprinting is a biometric technique for computing a unique profile associated to a physical person for \nauthentication purpose. It has been successfully applied also to software entities by using hash functions for \nintegrity checking after downloading. In the paper, we propose a fingerprinting algorithm to identify a \nmachine during a client-server authentication process. In detail, this host identifier can be used for \nconnecting to a database server without using an account storing a plain-text password. After the \npresentation of experimental results, we show some real scenarios where this solution can be applied.

The outsourcing of elaboration of data streams requires that a service provider collects and stores data on behalf of a company that does not have enough resources to sustain the efforts related to the management of such data streams. If a company does not trust the service provider, then it has to check the validity of the answers when querying the data store, since the results may be not reliable. In order to evaluate the answers, methods for approximate query processing can be used. These methods return fast answers based on data synopses. Such results can be used to validate those obtained by the providers on the basis of an accuracy estimation. In the paper, an extension of the traditional TPC-H benchmark has been used to compare three methods for approximate query processing, in order to verify the performance and the accuracy of the compared methods.

In web applications, databases are generally used as data repositories, where a server-side program interacts with a Database Management System (DBMS), retrieves content, and dynamically generates web pages. This is known as a three-layer architecture, that is widely exposed to database threats. The attacks are usually performed through the injection of SQL code in the forms of the web applications, exploiting the dynamic construction of SQL statements. So, the database security relies on the quality of the code and the controls done by the web developer in the application level. In this paper, we present a solution for the improvement of security of databases accebed by web applications. The security is based on a user modelling approach that completely relies on the authorization mechanism of DBMSs.

The standard benchmark for Decision Support Systems is TPC-H, which is composed of a database, a workload, and a set of metrics for the performance evaluation. However, TPC-H does not include a methodology for the benchmark of Approximate Query Answering Systems, or the software tools used to obtain fast answers to analytical queries in the decision making process. In the paper, the authors present a methodology to evaluate and compare Approximate Query Answering Systems. To this aim, a methodology that extends the standard TPC-H and a set of new metrics that take into account the specific features of these systems are proposed. Experimental results show the application of these metrics to two systems based on the data analytic approximation by orthonormal series.

Big Data Warehouses differ substantially from traditional data warehouses in that their schema should be based on novel logical models that allow more flexibility than that the relational model does. Furthermore, their design methodology also requires new principles, such as automation and agile techniques, in order to gain both a fast realization and reaction to changes in business requirements. In the paper, we discuss the new features of big data warehouses and present an innovative design methodology based on the key-value model.

A challenge in the recommender systems currently available for the tourism domain is how to suggest tourist itineraries in a specific geographical area (city or region). The proposed theoretical model allows items of intangible cultural heritage (events) such as processions, festivals, special markets, etc. to be characterized and correlated. The model features both a set of functions characterizing the events and a space-time relation that defines whether two events are correlated. The model allows itineraries to be constructed by computing the transitive closure of the space-time relation on the set of events. It can be used to construct itineraries at different grain sizes. This capacity makes the model scalable and easily applicable in the development of several applications. It has been implemented in a first order logic knowledge base in order to make an empirical evaluation of the model.