The rapid increase in Internet of Things (IoT) applications has raised security and privacy issues due to the huge amount of data acquired by IoT devices and transmitted through the Internet. Therefore, there is a need to understand what strategies should be applied to make IoT systems robust to security flaws and privacy weaknesses. In this paper, we first identify and discuss the best practices for IoT privacy and security, which include a set of procedures that can be taken as the guidelines to determine and solve privacy and security issues of IoT systems. Then, we follow and apply the identified best practices to two real IoT-based use cases: a crowding monitoring system and a vehicular mobility system. Finally, we computed the risk assessment score to evaluate the impact of the application of the identified best practices on the implemented IoT systems. We observe that following the proposed best practices the implemented IoT systems achieve an overall risk score of 1.3, which is from 215% to 361% lower than that achieved by comparable IoT systems proposed in the literature studies.
Privacy and Security Best Practices for IoT Solutions / Anedda, M.; Floris, A.; Girau, R.; Fadda, M.; Ruiu, P.; Farina, M.; Bonu, A.; Giusto, D. D.. - In: IEEE ACCESS. - ISSN 2169-3536. - 11:(2023), pp. 129156-129172. [10.1109/ACCESS.2023.3331820]
Privacy and Security Best Practices for IoT Solutions
Anedda M.;Fadda M.;Ruiu P.;
2023-01-01
Abstract
The rapid increase in Internet of Things (IoT) applications has raised security and privacy issues due to the huge amount of data acquired by IoT devices and transmitted through the Internet. Therefore, there is a need to understand what strategies should be applied to make IoT systems robust to security flaws and privacy weaknesses. In this paper, we first identify and discuss the best practices for IoT privacy and security, which include a set of procedures that can be taken as the guidelines to determine and solve privacy and security issues of IoT systems. Then, we follow and apply the identified best practices to two real IoT-based use cases: a crowding monitoring system and a vehicular mobility system. Finally, we computed the risk assessment score to evaluate the impact of the application of the identified best practices on the implemented IoT systems. We observe that following the proposed best practices the implemented IoT systems achieve an overall risk score of 1.3, which is from 215% to 361% lower than that achieved by comparable IoT systems proposed in the literature studies.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.