Secure and Scalable Internet of Medical Things using Ensemble Lightweight Cryptographic Model
Mounika Jammula, Venkata Mani Vakamulla, Sai Krishna Kondoju · 2023
Internet of medical things (IoMT) enables the users to transmit and receive the data over secured communication medium. IoMT devices handle sensitive patient data and information, making them attractive targets for cybercriminals. Ensuring the security and privacy of this data is critical to maintaining patient trust and preventing unauthorized access and data breaches. In general, the traditional encryption models such as symmetric, asymmetric, hash functions, and hybrid that includes advanced encryption standard (AES), RSA, elliptic curve cryptography, secure hash algorithm, and message digest algorithm etc. are designed to render high level security for communicating and storing data. However, they were not optimized for the use in IoMT devices, which have limited processing power, memory, and battery life. This led to the development of lightweight encryption algorithms, which are specifically designed to provide strong security while minimizing the computational and power requirements of IoT devices. Therefore, this work focused on implementation of lightweight-medical image cryptography (LW-MIC) system using ensemble lightweight cryptographic (ELWC) protocols. Initially, the medical image data from users is converted into digital data. Then, ELWC operation applied on vector data, which implements play-fair, and Cha-Cha based encryption algorithms. So, secured image data of users are transmitted over IoMT environment. Finally, the ELWC decryption algorithms are used to restore the original image data at the receiver (doctor) side. The simulation results revealed that the proposed LW-MIC system resulted in superior image encryption, reduced time complexity performance as compared to state of art methods.