The availability of large amounts of data is vital for the working of smart cities, which need to process heterogeneous information on citizens and the surrounding environment for enabling smart services. Since those data collections can include personal/sensitive information, ensuring security and privacy of the data collected and produced in a smart city is a key problem to be addressed. Two of the main pillars for protecting data privacy and security are anonymization and encryption, which however need to be carefully designed and adopted for ensuring effective protection while not compromising the possibility of performing analysis, a central aspect in smart cities. In this chapter, we address the problem of protecting large data collections in the context of smart cities, and illustrate possible approaches for effectively anonymizing data and for encrypting them, while permitting to perform computations.

Digital Infrastructure Policies for Data Security and Privacy in Smart Cities / S. De Capitani di Vimercati, S. Foresti, G. Livraga, P. Samarati - In: Smart Cities Policies and Financing : Approaches and Solutions / [a cura di] J. Vacca. - [s.l] : Elsevier, 2022. - ISBN 978-0-12-819130-9. - pp. 249-261 [10.1016/B978-0-12-819130-9.00007-3]

Digital Infrastructure Policies for Data Security and Privacy in Smart Cities

S. De Capitani di Vimercati;S. Foresti;G. Livraga;P. Samarati
2022

Abstract

The availability of large amounts of data is vital for the working of smart cities, which need to process heterogeneous information on citizens and the surrounding environment for enabling smart services. Since those data collections can include personal/sensitive information, ensuring security and privacy of the data collected and produced in a smart city is a key problem to be addressed. Two of the main pillars for protecting data privacy and security are anonymization and encryption, which however need to be carefully designed and adopted for ensuring effective protection while not compromising the possibility of performing analysis, a central aspect in smart cities. In this chapter, we address the problem of protecting large data collections in the context of smart cities, and illustrate possible approaches for effectively anonymizing data and for encrypting them, while permitting to perform computations.
Data security; data privacy; anonymization; encryption; collaborative computation
Settore INF/01 - Informatica
   Multi-Owner data Sharing for Analytics and Integration respecting Confidentiality and Owner control (MOSAICrOWN)
   MOSAICrOWN
   EUROPEAN COMMISSION
   H2020
   825333

   Machine Learning-based, Networking and Computing Infrastructure Resource Management of 5G and beyond Intelligent Networks (MARSAL)
   MARSAL
   EUROPEAN COMMISSION
   H2020
   101017171

   High quality Open data Publishing and Enrichment (HOPE)
   HOPE
   MINISTERO DELL'ISTRUZIONE E DEL MERITO
   2017MMJJRE_003
2022
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2434/897966
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