TY - GEN
T1 - Secure Time Series Data Sharing with Fine-Grained Access Control in Cloud-Enabled IIoT
AU - Halder, Subir
AU - Newe, Thomas
N1 - Publisher Copyright:
© 2022 IEEE.
PY - 2022
Y1 - 2022
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.This paper introduces SmartCrypt, a data storing and sharing system that supports 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 exhaustive 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 more than 17% query time, 32% range query time and improves 9% throughput 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.This paper introduces SmartCrypt, a data storing and sharing system that supports 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 exhaustive 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 more than 17% query time, 32% range query time and improves 9% throughput 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=85133188041&partnerID=8YFLogxK
U2 - 10.1109/NOMS54207.2022.9789834
DO - 10.1109/NOMS54207.2022.9789834
M3 - Conference contribution
AN - SCOPUS:85133188041
T3 - Proceedings of the IEEE/IFIP Network Operations and Management Symposium 2022: Network and Service Management in the Era of Cloudification, Softwarization and Artificial Intelligence, NOMS 2022
BT - Proceedings of the IEEE/IFIP Network Operations and Management Symposium 2022
A2 - Varga, Pal
A2 - Granville, Lisandro Zambenedetti
A2 - Galis, Alex
A2 - Godor, Istvan
A2 - Limam, Noura
A2 - Chemouil, Prosper
A2 - Francois, Jerome
A2 - Pahl, Marc-Oliver
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2022 IEEE/IFIP Network Operations and Management Symposium, NOMS 2022
Y2 - 25 April 2022 through 29 April 2022
ER -
