Agusti Solanas, Jens H Weber, Ayse Basar Bener, Frank van der Linden, Rafael Capilla

Description: This theme issue presents some of the most recent advances in and applications of software for context-aware and smart healthcare, so as to provide a view of the state of the technology.

Agusti Solanas, Domenec Puig, Aleix Ramirez, Josep M Mateo

Description: The design of algorithms and methods to control the movement of autonomous robots in unknown environments is a challenging task. The proper patterns of movement should be programmed into robots so as to make them explore the unknown space efficiently. In this article, we show that there exists a relation between the efficiency of the exploration and the degree of randomness of the trajectories followed by the robots. Specifically, we have carried out a number of simulations that point out that the more uniform the trajectories are, the more efficient the exploration.

Josep Domingo-Ferrer, Antoni Martínez-Ballesté, Josep Maria Mateo-Sanz, Francesc Sebé

The VLDB Journal 15 (4), 355-369

Description: Microaggregation is a family of methods for statistical disclosure control (SDC) of microdata (records on individuals and/or companies), that is, for masking microdata so that they can be released while preserving the privacy of the underlying individuals. The principle of microaggregation is to aggregate orig- inal database records into small groups prior to pub- lication. Each group should contain at least k records to prevent disclosure of individual information, where k is a constant value preset by the data protector. Re- cently, microaggregation has been shown to be useful to achieve k-anonymity, in addition to it being a good masking method. Optimal microaggregation (with mini- mum within-groups variability loss) can be computed in polynomial time for univariate data. Unfortunately, for multivariate data it is an NP-hard problem. Several heu- ristic approaches to microaggregation have been pro- posed in the literature. Heuristics yielding groups with fixed size k tends to be more efficient, whereas data- oriented heuristics yielding variable group size tends to result in lower information loss. This paper presents new data-oriented heuristics which improve on the trade-off between computational complexity and information loss and are thus usable for large datasets.

Francesc Sebé, Josep Domingo-Ferrer, Antoni Martinez-Balleste, Yves Deswarte, Jean-Jacques Quisquater

IEEE Transactions on Knowledge and Data Engineering 20 (8), 1034-1038

Description: Checking data possession in networked information systems such as those related to critical infrastructures (power facilities, airports, data vaults, defense systems, etc.) is a matter of crucial importance. Remote data possession checking protocols permit to check that a remote server can access an uncorrupted file in such a way that the verifier does not need to know beforehand the entire file that is being verified. Unfortunately, current protocols only allow a limited number of successive verifications or are impractical from the computational point of view. In this paper, we present a new remote data possession checking protocol such that: 1) it allows an unlimited number of file integrity verifications; 2) its maximum running time can be chosen at set-up time and traded off against storage at the verifier.

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