Enabling secure time-series data sharing via homomorphic encryption in cloud-assisted IIoT

A growing number of Industrial Internet of Things (IIoT) devices and services collect massive time -series data related to production, monitoring and maintenance. To provide ubiquitous access, scalability and sharing possibilities, the IIoT applications utilize the cloud to store collected data streams. However, secure storing of the massive and continuously generated data poses significant privacy risks, including data breaches for IIoT applications. Alongside, we need to protect the utility of the data streams by allowing benign services to access and run analytics securely and selectively. To address this, we propose SmartCrypt, a data storing and sharing system that supports scalable analytics over the encrypted time-series data. SmartCrypt enables users to secure and fine-grain shar-ing of their encrypted data. Additionally, SmartCrypt guarantees data confidentiality in the presence of unauthorized parties by allowing end-to-end encryption using a novel symmetric homomorphic encryption scheme. We perform extensive experiments on a real-world dataset primarily to assess the feasibility of SmartCrypt for secure storing and sharing of IIoT data streams. The results show that SmartCrypt reduces query time by 17%, reduces range query time by 32%, improves throughput by 9% and scalability by 20% over the best performed scheme in the state-of-the-art. (C) 2022 The Author(s). Published by Elsevier B.V.

Automated summary

Storing and sharing large-scale and continuously generated data in Industrial Internet of Things (IIoT) applications is a challenging issue. This article proposes SmartCrypt, a system that enables scalable analytics and data sharing through encrypted time-series data, while ensuring data confidentiality and security.