A hybrid logistic DNA-based encryption system for securing the Internet of Things patient monitoring systems

Abstract

The Internet of Things (IoT) plays a major role in healthcare, and high-end encryption schemes are needed to ensure data integrity and privacy in this industry. The security procedures and methodologies in the healthcare industry must be improved to combat various security breaches brought on by the IoT. The methodologies such as Advanced Encryption Systems (AES), Elliptic Curve Cryptography (ECC), and Data Encryption Schemes (DES) are used in IoT devices to ensure high-end security against counterfeit IoT attacks. The existing procedures and methodologies need brighter light of improvisation when transmitting medical data over the network. This study proposes a novel hybrid chaotic DNA and AES encryption methodology that combines the powerful features of 3D logistic chaotic maps and employs DNA operations in an AES system to provide more security against IoT attacks. Extensive experimentation is carried out using National Institute of Standard Technology (NIST) tests, and metrics tests such as Discrete Fourier Tests (DFT), Run length tests, and Frequency Monobit Tests are conducted and evaluated to determine the high randomness of the data and ensure high-security transmission. We show the suggested encryption technique outperforms the competing methods and is better suited for establishing high-level security for medical data transmission.