TY - JOUR
T1 - From trustworthy data to trustworthy IoT
T2 - A data collection methodology based on blockchain
AU - Ardagna, Claudio A.
AU - Asal, Rasool
AU - Damiani, Ernesto
AU - El Ioini, Nabil
AU - Elahi, Mehdi
AU - Pahl, Claus
N1 - Funding Information:
Ernesto Damiani is also with Università degli Studi di Milano. Research supported, in part, by EC H2020 Project CONCORDIA GA 830927 and Università degli Studi di Milano under the program “Piano sostegno alla ricerca 2019.” Authors’ addresses: C. A. Ardagna, DI, Università degli Studi di Milano, Milano, Italy; email: [email protected]; R. Asal, EBTIC, Khalifa University of Science, Technology and Research, Abu Dhabi, UAE; email: [email protected]; E. Dami-ani, C2PS, Khalifa University, Abu Dhabi, UAE; email: [email protected]; N. El Ioini, Free University of Bozen, Bolzano, Italy; email: [email protected]; M. Elahi, University of Bergen, Bergen, Norway; email: [email protected]; C. Pahl, Free University of Bozen, Bolzano, Italy; email: [email protected]. Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]. © 2020 Association for Computing Machinery. 2378-962X/2020/12-ART11 $15.00 https://doi.org/10.1145/3418686
Funding Information:
Research supported, in part, by EC H2020 Project CONCORDIA GA 830927 and Universit? degli Studi di Milano under the program ?Piano sostegno alla ricerca 2019.?
Publisher Copyright:
© 2020 Association for Computing Machinery.
PY - 2021/1
Y1 - 2021/1
N2 - Internet of Things (IoT) is composed of physical devices, communication networks, and services provided by edge systems and over-the-top applications. IoT connects billions of devices that collect data from the physical environment, which are pre-processed at the edge and then forwarded to processing services at the core of the infrastructure, on top of which cloud-based applications are built and provided to mobile end users. IoT comes with important advantages in terms of applications and added value for its users, making their world smarter and simpler. These advantages, however, are mitigated by the difficulty of guaranteeing IoT trustworthiness, which is still in its infancy. IoT trustworthiness is a must especially in critical domains (e.g., health, transportation) where humans become new components of an IoT system and their life is put at risk by system malfunctioning or breaches. In this article, we put forward the idea that trust in IoT can be boosted if and only if its automation and adaptation processes are based on trustworthy data. We therefore depart from a scenario that considers the quality of a single decision as the main goal of an IoT system and consider the trustworthiness of collected data as a fundamental requirement at the basis of a trustworthy IoT environment. We therefore define a methodology for data collection that filters untrusted data out according to trust rules evaluating the status of the devices collecting data and the collected data themselves. Our approach is based on blockchain and smart contracts and collects data whose trustworthiness and integrity are proven over time. The methodology balances trustworthiness and privacy and is experimentally evaluated in real-world and simulated scenarios using Hyperledger fabric blockchain.
AB - Internet of Things (IoT) is composed of physical devices, communication networks, and services provided by edge systems and over-the-top applications. IoT connects billions of devices that collect data from the physical environment, which are pre-processed at the edge and then forwarded to processing services at the core of the infrastructure, on top of which cloud-based applications are built and provided to mobile end users. IoT comes with important advantages in terms of applications and added value for its users, making their world smarter and simpler. These advantages, however, are mitigated by the difficulty of guaranteeing IoT trustworthiness, which is still in its infancy. IoT trustworthiness is a must especially in critical domains (e.g., health, transportation) where humans become new components of an IoT system and their life is put at risk by system malfunctioning or breaches. In this article, we put forward the idea that trust in IoT can be boosted if and only if its automation and adaptation processes are based on trustworthy data. We therefore depart from a scenario that considers the quality of a single decision as the main goal of an IoT system and consider the trustworthiness of collected data as a fundamental requirement at the basis of a trustworthy IoT environment. We therefore define a methodology for data collection that filters untrusted data out according to trust rules evaluating the status of the devices collecting data and the collected data themselves. Our approach is based on blockchain and smart contracts and collects data whose trustworthiness and integrity are proven over time. The methodology balances trustworthiness and privacy and is experimentally evaluated in real-world and simulated scenarios using Hyperledger fabric blockchain.
KW - Blockchain
KW - Internet of Things
KW - Trustworthiness
UR - http://www.scopus.com/inward/record.url?scp=85100300342&partnerID=8YFLogxK
U2 - 10.1145/3418686
DO - 10.1145/3418686
M3 - Article
AN - SCOPUS:85100300342
SN - 2378-962X
VL - 5
JO - ACM Transactions on Cyber-Physical Systems
JF - ACM Transactions on Cyber-Physical Systems
IS - 1
M1 - 11
ER -