A Novel Lightweight Encryption Model for IoT Healthcare Data Security at Fog Layer: A Hybrid Approach Using Attribute-Based Encryption and Homomorphic Encryption

Abstract

The quality of people's lives has risen because of the Internet of Things (IoT), as it connects billions of things worldwide. New methods in order to analyse patient data in the healthcare industry have been developed as a result of IoT development and innovation.

Although having a crucial function in the transfer of medical data, the Internet of Things (IoT) also raises security risks to the health data, that is particularly unique to a patient, is required for remote medical treatment. Current technologies for analysing and transforming patient data involve cloud and IoT-based platforms. When processing incredibly large amounts of data, cloud computing encounters network usage and latency issues. Fog layers have been used to improve the capabilities of IoT-based healthcare systems, and they have proven valuable by offering quick response times and low latency.However,Such a trend is making it extremely difficult to protect users' privacy, which goes some way towards resolving security and privacy concerns.This article introduces a fog assisted  framework to secure IoT driven  healthcare systems.It presents a hybrid encryption model for securing IoT healthcare data at the fog layer, combining modified Attribute-Based Encryption (ABE) with partial Homomorphic Encryption (HE). Our approach addresses the key challenges of data security, privacy, and computational efficiency in IoT healthcare systems. The proposed model demonstrates significant improvements in processing time (37% faster), energy consumption (45% reduction), and security strength compared to existing solutions. Experimental results show that our hybrid approach achieves optimal performance for resource-constrained IoT devices while maintaining robust security standards.