Today, Internet of Things (IoT) implements an ecosystem where a panoply of interconnected devices collect data from physical environments and supply them to processing services, on top of which cloud-based applications are built and provided to mobile end users. The undebatable advantages of smart IoT systems clash with the need of a secure and trustworthy environment. In this paper, we propose a service-based methodology based on blockchain and smart contracts for trustworthy evidence collection at the basis of a trustworthy IoT assurance evaluation. The methodology balances the provided level of trustworthiness and its performance, and is experimentally evaluated using Hyperledger fabric blockchain.

Trustworthy IoT: An evidence collection approach based on smart contracts / C.A. Ardagna, R. Asal, E. Damiani, N. El Ioini, C. Pahl - In: 2019 IEEE International Conference on Services Computing (SCC)[s.l] : IEEE, 2019. - ISBN 9781728127200. - pp. 46-50 (( convegno Conference on Services Computing tenutosi a Milano nel 2019 [10.1109/SCC.2019.00020].

Trustworthy IoT: An evidence collection approach based on smart contracts

C.A. Ardagna;E. Damiani;
2019

Abstract

Today, Internet of Things (IoT) implements an ecosystem where a panoply of interconnected devices collect data from physical environments and supply them to processing services, on top of which cloud-based applications are built and provided to mobile end users. The undebatable advantages of smart IoT systems clash with the need of a secure and trustworthy environment. In this paper, we propose a service-based methodology based on blockchain and smart contracts for trustworthy evidence collection at the basis of a trustworthy IoT assurance evaluation. The methodology balances the provided level of trustworthiness and its performance, and is experimentally evaluated using Hyperledger fabric blockchain.
Assurance Evaluation; Blockchain; IoT
Settore INF/01 - Informatica
   Cyber security cOmpeteNce fOr Research anD Innovation (CONCORDIA)
   CONCORDIA
   EUROPEAN COMMISSION
   H2020
   830927
2019
IEEE
IEEE Computer Society (CS)
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2434/686964
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