Agusti Solanas, Enrique Romero, Sergio Gómez, Josep M. Sopena, Rene Alquézar, Josep Domingo-Ferrer

Artificial Intelligence Research and Development 131 (CCIA), 41

Description: This paper presents a new feature selection method and an outliers detection algorithm. The presented method is based on using a genetic algorithm combined with a problem-specific-designed neural network. The dimensional reduction and the outliers detection makes the resulting dataset more suitable for training neural networks. A comparative analysis between different kind of proposed criteria to select the features is reported. A number of experimental results have been carried out to demonstrate the usefulness of the presented technique.

Athanasios Zigomitros, Fran Casino, Agusti Solanas, Constantinos Patsakis

IEEE Access 8, 51071-51099

Description: Recent advances in telecommunications and database systems have allowed the scientific community to efficiently mine vast amounts of information worldwide and to extract new knowledge by discovering hidden patterns and correlations. Nevertheless, all this shared information can be used to invade the privacy of individuals through the use of fusion and mining techniques. Simply removing direct identifiers such as name, SSN, or phone number is not anymore sufficient to prevent against these practices. In numerous cases, other fields, like gender, date of birth and/or zipcode, can be used to re-identify individuals and to expose their sensitive details, e.g. their medical conditions, financial statuses and transactions, or even their private connections. The scope of this work is to provide an in-depth overview of the current state of the art in Privacy-Preserving Data Publishing (PPDP) for relational data. To counter information leakage, a number of data anonymisation methods have been proposed during the past few years, including k-anonymity, l-diversity, t-closeness, to name a few. In this study we analyse these methods providing concrete examples not only to explain how each of them works, but also to facilitate the reader to understand the different usage scenarios in which each of them can be applied. Furthermore, we detail several attacks along with their possible countermeasures, and we discuss open questions and future research directions.

Constantinos Patsakis, Kleanthis Dellios, Jose Maria De Fuentes, Fran Casino, Agusti Solanas

Journal of Hardware and Systems Security 3 (3), 289-303

Description: Asthevehiclesaregraduallytransformedintotheconnected-vehicles, standard features of the past (i.e. immobilizer, keyless entry, self-diagnostics) were neglected to be software updated and hardware upgraded so they do not “align” with the cyber-security demands of the new ICT era (IoT, Indus- try 4.0, IPv6, sensor technology) we have stepped into, therefore introducing critical legacy IT security issues. Stepping beyond the era of common auto- theft and “chop-shops”, the new wave of attackers have cyber-skills to exploit these vulnerabilities and steal the vehicle or manipulate it. Recent evolution in ICT offered automotive industry vital tools for vehicle safety, functionality and up to 2010, theft prevention. However, the same technologies are the ones that make vehicles prone to cyber-attacks. To counter such attacks, this work proposes a unified solution that logs all hardware profile changes of a vehi- cle in a blockchain, to manage control and allow only authenticated changes, subject to user, time, geospatial and contextual constraints exploiting several blockchain features. Testing of the proposed solution omens the prevention of numerous commons attacks, while additionally provides forensics capabilities and significantly enhancing the security architecture of the vehicle (respecting the original IT architectural design of automotive manufacturers).

Fran Casino, Constantinos Patsakis, Agusti Solanas

Electronic Commerce Research and Applications 38, 100895

Description: The amount of available information is growing steadily and, as a result, Internet users benefit from recommender systems, which help them find information, services and products that best fit their needs. A common technique used in recommender systems is Collaborative Filtering, which is based on users’ collaboration to make recommendations. However, users are getting more concerned about their privacy and can be reluctant to disclose their interests and other personal information. Hence, with the aim to foster users collaboration, the development of privacy-aware collaborative filtering methods has become a hot topic in the field. In this article we recall the concept of Privacy-Preserving Collaborative Filtering (PPCF) and introduce a novel approach based on variable-group-size microaggregation, which provides k-anonymity to the users. Also, we introduce several new metrics based on users’ behaviour that overcome the drawbacks of traditional metrics. Extensive experiments show that our approach can provide more accurate recommendations than well-known methods while, at the same time, preserving users’ privacy.

Carlos E Jiménez, Francisco Falcone, Agusti Solanas, Héctor Puyosa, Saleem Zoughbi, Federico González

Handbook of Research on Democratic Strategies and Citizen-Centered E-Government Services, 1

Description: The advent of Smart Cities is one of the greatest challenges and field of opportunities in the goal to achieve sustainable, comfortable, and socially responsible living environments. A large number of factors, spanning from government/administration/citizen interaction models, heterogeneous communication network, interoperability, or security determine the capabilities and functionalities that can be deployed. In this chapter, different factors in the implementation and adoption of E-Government within Smart City scenarios are described. The authors include the Interoperability Principle as a part of the Open Government concept and link this concept with the Smart Cities view. Then, they describe a new model of public organization that they call “Intelligent,” characterized by the “Smart Government,” and they propose a matrix with the elements of this model. Then, the authors analyze the technical and infrastructure dimensions of the matrix.

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