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  • Eugenio Gianniti e Danilo Ardagna - Politecnico di Milano, Milan, Italy
  • Li Zhang - IBM T. J. Watson Research Center, NY, USA

Recent years saw an increasing success in the application of deep learning methods across various domains and for tackling different problems, ranging from image recognition and classification to text processing and speech recognition. In this paper we propose and validate an approach to model the execution time for training convolutional neural...

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  • Hebert Silva, Tania Basso, Regina Moraes - University of Campinas, Limeira, Brazil
  • Donatello Elia, Sandro Fiore - Euro-Mediterranean Center for Climate Change (CMCC), Lecce, Italy

Preserving individual privacy is one of the major issues in the context of Big Data, since handling huge volumes of data may contribute to the disclosure of sensitive or personally identifiable information. In fact, even when data is anonymized there is a risk of re-identification through privacy attacks. This paper presents a re-identification risk-based anonymization...

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Authors: Claudia Morgadoy, Gisele Busichia Baioco, Tania Basso, Regina Moraes - University of Campinas, Limeira, Brazil

Nowadays, organizations collect vast amounts of data for future analysis. Motivated by this amount of data and requirements of Web2.0, a plethora of non-relational databases (NoSQL) emerged in recent years. However, several security features in relational databases (e.g., access control) have been left in non-relational management systems to be developed by the application, which can raise security breaches. This paper proposes a security model, based on the use of...

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Authors: Francisco Brasileiro and Andrey Brito, from Department of Systems and Computing Universidade Federal de Campina Grande Ignacio Blanquer, Institute of Instrumentation for Molecular Imaging (I3M) Universitat Politecnica de Valencia - CSIC

This paper describes the goals of the ATMOSPHERE project, which is a multi-institutional research and development (R&D) effort aiming at designing and implementing a framework and platform to develop, build, deploy, measure and evolve trustworthy, cloud-enabled applications. The proposed system should address the federation of geographically distributed cloud computing providers that rely on lightweight virtualization, and provide access to heterogeneous sets of resources. We discuss some preliminary results, including the architecture that has been proposed to address these challenges...

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Authors: Tania Basso and Regina Moraes (University of Campinas), Nuno Antunes and Marco Vieira (University of Coimbra)

Frequently users have to provide personal information for being able to use web applications and services. They are commonly confronted with a privacy policy that they must accept, implicitly trusting the provider organization to protect their privacy. The recent trend to develop frameworks for privacy policy definition has moved the state-of-the-art forward, but did not solve the main problems: allow users to express their privacy requirements and assure that these requirements will be enforced. This paper discusses the main challenges towards the development of privacy-aware web...

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  • Danilo Ardagna (POLIMI), Ignacio Blanquer, Miguel Caballer, Amanda Calatrava (UPV) and Marco Vieira (UC)
  • Francisco Brasileiro, Reinaldo Gomes (UFCG) and Wagner Meira Jr. (UFMG) - Brazil

Trustworthiness in data analytics and cloud services comprises a broad range of properties. Dimensions such as Security, Privacy protection, Quality of Services, Reliability, and Fairness impose tackling a set of challenges at different layers. ATMOSPHERE has designed a software architecture to provide performance simulation...

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