Panel on “Past and future of computer science theory”

The twenty-ninth edition of the SEBD (Italian Symposium on Advanced Database Systems), held on 5-9 September 2021 in Pizzo (Calabria Region, Italy), included a joint seminar on “Reminiscence of TIDB 1981” with invited talks given by some of the participants to the Advanced Seminar on Theoretical Issues in Databases (TIDB), which took place in the same region exactly forty years earlier. The joint seminar was concluded by a Panel on “The Past and the Future of Computer Science Theory” with the participation of four distinguished computer science theorists (Ronald Fagin, Georg Gottlob, Christos Papadimitriou and Moshe Vardi), who were interviewed by Giorgio Ausiello, Maurizio Lenzerini, Luigi Palopoli, Domenico Saccà and Francesco Scarcello. This paper reports the summaries of the four interviews

SoK: Cryptographically Protected Database Search

Protected database search systems cryptographically isolate the roles of reading from, writing to, and administering the database. This separation limits unnecessary administrator access and protects data in the case of system breaches. Since protected search was introduced in 2000, the area has grown rapidly; systems are offered by academia, start-ups, and established companies. However, there is no best protected search system or set of techniques. Design of such systems is a balancing act between security, functionality, performance, and usability. This challenge is made more difficult by ongoing database specialization, as some users will want the functionality of SQL, NoSQL, or NewSQL databases. This database evolution will continue, and the protected search community should be able to quickly provide functionality consistent with newly invented databases. At the same time, the community must accurately and clearly characterize the tradeoffs between different approaches. To address these challenges, we provide the following contributions: 1) An identification of the important primitive operations across database paradigms. We find there are a small number of base operations that can be used and combined to support a large number of database paradigms. 2) An evaluation of the current state of protected search systems in implementing these base operations. This evaluation describes the main approaches and tradeoffs for each base operation. Furthermore, it puts protected search in the context of unprotected search, identifying key gaps in functionality. 3) An analysis of attacks against protected search for different base queries. 4) A roadmap and tools for transforming a protected search system into a protected database, including an open-source performance evaluation platform and initial user opinions of protected search.Comment: 20 pages, to appear to IEEE Security and Privac

Economic data bank management in a developing nation

This dissertation describes the results of a research project which was undertaken at Loughborough University of Technology. The basic objectives of the research project were: (1) to investigate the management elements required for organising the development of an Economic Data Bank (EDB), with particular emphasis on the requirements of a developing nation; (2) to investigate the sociological, political and technical implications associated with organising the development of an EDB in a developing nation. A theoretical framework was established for this study. This was dene after an extensive search and review of literature was performed in the areas of data and data base management systems, management information systems, and computer technology in general. [Continues.

Archiving scientific data

We present an archiving technique for hierarchical data with key structure. Our approach is based on the notion of timestamps whereby an element appearing in multiple versions of the database is stored only once along with a compact description of versions in which it appears. The basic idea of timestamping was discovered by Driscoll et. al. in the context of persistent data structures where one wishes to track the sequences of changes made to a data structure. We extend this idea to develop an archiving tool for XML data that is capable of providing meaningful change descriptions and can also efficiently support a variety of basic functions concerning the evolution of data such as retrieval of any specific version from the archive and querying the temporal history of any element. This is in contrast to diff-based approaches where such operations may require undoing a large number of changes or significant reasoning with the deltas. Surprisingly, our archiving technique does not incur any significant space overhead when contrasted with other approaches. Our experimental results support this and also show that the compacted archive file interacts well with other compression techniques. Finally, another useful property of our approach is that the resulting archive is also in XML and hence can directly leverage existing XML tools

Joining Entities Across Relation and Graph with a Unified Model

This paper introduces RG (Relational Genetic) model, a revised relational model to represent graph-structured data in RDBMS while preserving its topology, for efficiently and effectively extracting data in different formats from disparate sources. Along with: (a) SQL$_\delta$, an SQL dialect augmented with graph pattern queries and tuple-vertex joins, such that one can extract graph properties via graph pattern matching, and "semantically" match entities across relations and graphs; (b) a logical representation of graphs in RDBMS, which introduces an exploration operator for efficient pattern querying, supports also browsing and updating graph-structured data; and (c) a strategy to uniformly evaluate SQL, pattern and hybrid queries that join tuples and vertices, all inside an RDBMS by leveraging its optimizer without performance degradation on switching different execution engines. A lightweight system, WhiteDB, is developed as an implementation to evaluate the benefits it can actually bring on real-life data. We empirically verified that the RG model enables the graph pattern queries to be answered as efficiently as in native graph engines; can consider the access on graph and relation in any order for optimal plan; and supports effective data enrichment.Comment: 24 pages, 16 figures, 5 table

Preference rules for label ranking: Mining patterns in multi-target relations

In this paper, we investigate two variants of association rules for preference data, Label Ranking Association Rules and Pairwise Association Rules. Label Ranking Association Rules (LRAR) are the equivalent of Class Association Rules (CAR) for the Label Ranking task. In CAR, the consequent is a single class, to which the example is expected to belong to. In LRAR, the consequent is a ranking of the labels. The generation of LRAR requires special support and confidence measures to assess the similarity of rankings. In this work, we carry out a sensitivity analysis of these similarity-based measures. We want to understand which datasets benefit more from such measures and which parameters have more influence in the accuracy of the model. Furthermore, we propose an alternative type of rules, the Pairwise Association Rules (PAR), which are defined as association rules with a set of pairwise preferences in the consequent. While PAR can be used both as descriptive and predictive models, they are essentially descriptive models. Experimental results show the potential of both approaches.This research has received funding from the ECSEL Joint Undertaking, the framework programme for research and innovation horizon 2020 (2014-2020) under grant agreement number 662189-MANTIS-2014-1, and by National Funds through the FCT — Fundação para a Ciência e a Tecnologia (Portuguese Foundation for Science and Technology) as part of project UID/EEA/50014/2013