A Novel Lightweight Encryption Choatic Scheme for IOT based Healthcare Systems

Abstract

The Internet of Things (IoT) exhibits a crucial position in enabling smarter devices and establishing new communication channels between humans and machines via the Internet. Smart gadgets are widely used across sectors such as healthcare, automation, smart homes, and other user-assisted applications. While sensor-driven devices have significantly enhanced daily life, many IoT infrastructures suffer from security vulnerabilities that compromise privacy. Recently, the Advanced Encryption Standard (AES) has emerged as a promising area of research for securing IoT healthcare devices. However, encrypted data remains a target for various IoT attacks, necessitating further improvements in security measures. Motivated by these security concerns, this study proposes a novel lightweight encryption scheme called Biscroll maps. This scheme integrates dynamic dual logistic maps based on chaos theory into a three-dimensional substitution box (S-Box) to enhance data confidentiality, availability, and integrity. The proposed scheme has applicability of  the DNA computing over the traditional S-Box operations such as permutations and shifting .  The implemented system operates within an IoT infrastructure designed for real-time data collection from diverse sources. Rigorous experimentation has assessed the effectiveness of the proposed methodologies, including security evaluations such as NIST and S-box tests. Additionally, the performance of these methodologies has been benchmarked against existing encryption schemes in terms of time and memory usage. Results from the experiments indicate that the newly introduced L-DAL-SBoX algorithm surpasses other existing algorithms, establishing itself as a robust solution for IoT security.