Verifiable fully outsourced attribute-based signcryption system for IoT eHealth big data in cloud computing

Area of Science:

• Computer Science
• Information Security
• Healthcare Technology

Background:

• The proliferation of Internet of Things (IoT) in healthcare has led to a surge in eHealth big data.
• Cloud computing offers scalable storage but raises concerns regarding data privacy and security due to data residing outside the owner's physical control.
• Attribute-based signcryption (ABSC) provides cryptographic solutions for fine-grained access control, authentication, confidentiality, and data owner privacy.

Purpose of the Study:

• To propose an efficient and secure attribute-based signcryption (ABSC) scheme tailored for resource-constrained IoT devices in healthcare.
• To address the computational burden of complex cryptographic operations on IoT devices by leveraging cloud computing resources.
• To ensure the privacy and security of sensitive eHealth data generated by IoT devices.

Main Methods:

• Developed a novel ABSC scheme that outsources computationally intensive tasks (key generation, signcryption, designcryption) to a cloud server.
• Implemented a trusted attribute authority, signcryptor, and designcryptor model for task delegation.
• Incorporated an outsourcing verification server to validate the correctness of cloud-based computations.

Main Results:

• The proposed scheme significantly reduces the computational load on local IoT devices by offloading complex operations to the cloud.
• Security analysis and comparative evaluations demonstrate the efficiency and effectiveness of the scheme.
• Simulations confirm the scheme's suitability for resource-constrained IoT environments, balancing security with performance.

Conclusions:

• The developed ABSC scheme offers an efficient and secure solution for protecting eHealth data in IoT environments.
• Outsourcing heavy computations to the cloud, with verification, is a viable strategy for enhancing security on low-power IoT devices.
• The proposed method is well-suited for practical applications in the healthcare IoT domain, ensuring data privacy and integrity.