Privacy-Preserving Broker-ABE Scheme for Multiple Cloud-Assisted Cyber Physical Systems

Area of Science:

• Cyber-Physical Systems
• Cloud Computing
• Information Security

Background:

• Cloud-assisted cyber-physical systems (CCPSs) integrate physical processes with cloud computing for data analysis.
• Securing data communication between numerous sensors and diverse cloud service providers (CSPs) is crucial.
• Attribute-based encryption (ABE) is a suitable technique for managing access control in such distributed environments.

Purpose of the Study:

• To propose a novel privacy-preserving broker-attribute-based encryption (ABE) scheme tailored for multiple CCPSs (MCCPS).
• To enhance data security and privacy for sensor data transmitted to various CSPs.
• To address the computational limitations of sensors by optimizing the ABE process.

Main Methods:

• Developed a broker-ABE scheme that separates policy embedding from the core ABE operations.
• Offloaded the computationally intensive policy embedding task from resource-constrained sensors to more powerful brokers.
• Implemented a mechanism for CSPs to safeguard data privacy against external coercion.

Main Results:

• The proposed scheme effectively secures data communication in MCCPS environments.
• Policy embedding is efficiently handled by brokers, reducing sensor workload.
• Enhanced data privacy protection is provided for CSPs against external threats.

Conclusions:

• The broker-ABE scheme offers a robust solution for privacy preservation in MCCPS.
• This approach balances security requirements with the computational constraints of IoT devices.
• It facilitates secure data sharing across multiple cloud platforms while maintaining user privacy.