Enhanced Security Measures for Medical IoT Communication through Biological Feature-Based Elliptic Curve Cryptography Authentication

Medical IoT devices often collect, transmit, and communicate sensitive patient health data. Ensuring robust security measures is essential to protect patient privacy and confidentiality during data transmission. Unauthorized access to this data can lead to privacy breaches, identity theft, or misuse of personal health information. Many researchers are trying to develop secure communication for medical IoT devices. Conventional methods, such as RSA-based authentication, require more data space and processing time, posing challenges for resource-constrained medical IoT devices. Additionally, the traditional system provides a single level of security and focuses only on internal control techniques. To overcome these limitations, a double level of security and external error control techniques-based authentication algorithm is proposed. The proposed authentication employs Elliptic Curve Cryptography (ECC) and DNA computing techniques combined to solve the memory space problem and processing time, respectively. Here ECC helps to encrypt the medical document using the private key and public key data to provide a double level of security while performing the authentication process. Also, the DNA computing technique is used to encode the original medical content since it has the capacity to store a large amount of data. From the simulation results, the proposed ECC-based double-level encryption process uses only a limited amount of time to execute both the encryption and decryption time. It also shows that the proposed authentication algorithm requires a lesser number of communication bits and a lesser storage amount of data compared with other traditional methods.