TY - JOUR
T1 - Enabling secure time-series data sharing via homomorphic encryption in cloud-assisted IIoT
AU - Halder, Subir
AU - Newe, Thomas
N1 - Publisher Copyright:
© 2022 The Author(s)
PY - 2022/8
Y1 - 2022/8
N2 - 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 sharing 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.
AB - 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 sharing 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.
KW - Access control
KW - Data security
KW - Homomorphic encryption
KW - Industrial IoT
KW - Secure sharing
KW - Time-series data
UR - http://www.scopus.com/inward/record.url?scp=85127725801&partnerID=8YFLogxK
U2 - 10.1016/j.future.2022.03.032
DO - 10.1016/j.future.2022.03.032
M3 - Article
AN - SCOPUS:85127725801
SN - 0167-739X
VL - 133
SP - 351
EP - 363
JO - Future Generation Computer Systems
JF - Future Generation Computer Systems
ER -