Our smart society strongly relies on data, which are continuously generated, collected, stored, and processed by millions of connected IoT devices and smart sensors. Such data are at the basis of typically complex decision-making processes that require advanced analytics. Due to the vast and increasing amount of data, their storage and processing are often outsourced to third parties (e.g., service providers and decentralized computational services) that might be not fully trustworthy in their operating. In this chapter, we focus on the problem of assessing integrity of query computations involving external service providers, and illustrate possible approaches for enabling the verification of the integrity of query results. We will cover both deterministic approaches, based on the definition of authenticated data structures over the data and giving full integrity guarantees, and probabilistic approaches, based on the insertion of control information in the data and providing probabilistic integrity guarantees.

Query Integrity in Smart Environments / S. De Capitani di Vimercati, S. Foresti, P. Samarati (LECTURE NOTES IN COMPUTER SCIENCE). - In: Security and Privacy in Smart Environments / [a cura di] N. Pitropakis, S. Katsikas. - [s.l] : Springer, 2025. - ISBN 978-3-031-66707-7. - pp. 25-48 [10.1007/978-3-031-66708-4_2]

Query Integrity in Smart Environments

S. De Capitani di Vimercati;S. Foresti;P. Samarati
2025

Abstract

Our smart society strongly relies on data, which are continuously generated, collected, stored, and processed by millions of connected IoT devices and smart sensors. Such data are at the basis of typically complex decision-making processes that require advanced analytics. Due to the vast and increasing amount of data, their storage and processing are often outsourced to third parties (e.g., service providers and decentralized computational services) that might be not fully trustworthy in their operating. In this chapter, we focus on the problem of assessing integrity of query computations involving external service providers, and illustrate possible approaches for enabling the verification of the integrity of query results. We will cover both deterministic approaches, based on the definition of authenticated data structures over the data and giving full integrity guarantees, and probabilistic approaches, based on the insertion of control information in the data and providing probabilistic integrity guarantees.
deterministic techniques; probabilistic techniques; Query integrity
Settore INFO-01/A - Informatica
   Edge AI Technologies for Optimised Performance Embedded Processing (EdgeAI)
   EdgeAI
   MINISTERO DELLO SVILUPPO ECONOMICO
   101097300

   Green responsibLe privACy preservIng dAta operaTIONs
   GLACIATION
   EUROPEAN COMMISSION
   101070141

   POLAR: POLicy specificAtion and enfoRcement for privacy-enhanced data management
   POLAR
   MINISTERO DELL'UNIVERSITA' E DELLA RICERCA
   2022LA8XBH_001

   SEcurity and RIghts in the CyberSpace (SERICS)
   SERICS
   MINISTERO DELL'UNIVERSITA' E DELLA RICERCA
   codice identificativo PE00000014
2025
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2434/1144417
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