A Chaos Based Security Approach for Data Authentication in Personal and Body Area Networks

Personal Area Networks (PANs) and Body Area Networks (BANs) are localized networks designed to facilitate communication between personal devices and sensors, often within a short range. PANs typically connect devices like smartphones, tablets, and wearables, while BANs are specialized networks that connect sensors directly on or near the human body. These networks are pivotal in applications ranging from health monitoring to fitness tracking and personal productivity. However, due to the sensitive nature of data transmitted, especially in BANs, securing these networks is crucial to protect user privacy and prevent unauthorized access to potentially sensitive information. This paper present a Chaos based approach for generating a pseudo random (PR) sequence based on Physiological inter pulse interval (IPI) collected from the subject. The evaluation of the strength of the PR sequence is gauged based on the hamming distance and entropy metrics. It has been shown that the proposed approach attains a higher hamming distance and entropy compared to exiting work in the domain.