Privacy-by-design in big data analytics and social mining (Rapporti tecnici/preprint/working paper)

Type

• Prodotto della ricerca (Classe)
• Rapporti tecnici/preprint/working paper (Classe)

Label

• Privacy-by-design in big data analytics and social mining (Rapporti tecnici/preprint/working paper) (literal)

Anno

• 2013-01-01T00:00:00+01:00 (literal)

Alternative label

• Monreale A., Rinzivillo S., Pratesi F., Giannotti F., Pedreschi D. (2013)
  Privacy-by-design in big data analytics and social mining
  
  (literal)

Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#autori

• Monreale A., Rinzivillo S., Pratesi F., Giannotti F., Pedreschi D. (literal)

Note

• PuMa (literal)

Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#supporto

• Altro (literal)

Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#affiliazioni

• Computer Science Department, University of Pisa, Italy; CNR-ISTI, Pisa, Italy; Computer Science Department, University of Pisa, Italy; CNR-ISTI, Pisa, Italy; Computer Science Department, University of Pisa, Italy. (literal)

Titolo

• Privacy-by-design in big data analytics and social mining (literal)

Abstract

• Privacy is ever-growing concern in our society: the lack of reliable privacy safeguards in many current services and devices is the basis of a diffusion that is often more limited than expected. Moreover, people feel reluctant to provide true personal data, unless it is absolutely necessary. Thus, privacy is becoming a fundamental aspect to take into account when one wants to use, publish and analyze data involving sensitive information. Unfortunately, it is increasingly hard to transform the data in a way that it protects sensitive information: we live in the era of big data characterized by unprecedented opportunities to sense, store and analyze social data describing human activities in great detail and resolution. As a result privacy preservation simply cannot be accomplished by de-identification. In this paper, we propose the privacy-by-design paradigm to develop technological frameworks for countering the threats of undesirable, unlawful effects of privacy violation, without obstructing the knowledge discovery opportunities of social mining and big data analytical technologies. Our main idea is to inscribe privacy protection into the knowledge discovery technology by design, so that the analysis incorporates the relevant privacy requirements from the start. (literal)

Prodotto di

• Knowledge Discovery and Data Mining (ICT.P08.009.003) (Modulo)
• Istituto di scienza e tecnologie dell'informazione \"Alessandro Faedo\" (ISTI) (Istituto)

Autore CNR

• SALVATORE RINZIVILLO (Persona)
• FOSCA GIANNOTTI (Unità di personale interno)

Insieme di parole chiave

• Parole chiave di "Privacy-by-design in big data analytics and social mining" (Insieme di parole chiave)

Incoming links:

Prodotto

• Istituto di scienza e tecnologie dell'informazione \"Alessandro Faedo\" (ISTI) (Istituto)
• Knowledge Discovery and Data Mining (ICT.P08.009.003) (Modulo)

Autore CNR di

• FOSCA GIANNOTTI (Unità di personale interno)
• SALVATORE RINZIVILLO (Persona)

Insieme di parole chiave di

• Parole chiave di "Privacy-by-design in big data analytics and social mining" (Insieme di parole chiave)