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International Journal of Advanced Computer Science and Applications(IJACSA), Volume 15 Issue 8, 2024.
Abstract: The expansion of Internet of Things (IoT) applications, such as wireless sensor networks, intelligent devices, Internet technologies, and machine-to-machine interaction, has changed current information technology in recent decades. The IoT enables the exchange of information and communication between items via an internal network. Nevertheless, the advancement of technology raises the urgent issue of ensuring data privacy and security, particularly in critical sectors like healthcare. This study aims to address the problem by developing a hybrid security scheme that combines the Secure Hash Algorithm (SHA-256), Rivest Cipher 4 (RC4), and Elliptic Curve Digital Signature Scheme (ECDSS) to ensure the confidentiality and integrity of medical data transmitted by IoT-enabled healthcare systems. This hybrid model employs the Elliptic Curve Digital Signature Scheme (ECDSS) to perform exclusive OR (XOR) operations inside the RC4 encryption algorithm. This enhances the RC4 encryption process by manipulating the encryption key. Moreover, SHA-256 is used to convert incoming data in order to guarantee data security. An empirical investigation validates the superiority of the suggested model. This framework attains a data transfer rate of 11.67 megabytes per millisecond, accompanied by an encryption duration of 846 milliseconds and a decryption duration of 627 milliseconds.
Longyang Du and Tian Xie, “Towards Secure Internet of Things-Enabled Healthcare: Integrating Elliptic Curve Digital Signatures and Rivest Cipher Encryption” International Journal of Advanced Computer Science and Applications(IJACSA), 15(8), 2024. http://dx.doi.org/10.14569/IJACSA.2024.0150858
@article{Du2024,
title = {Towards Secure Internet of Things-Enabled Healthcare: Integrating Elliptic Curve Digital Signatures and Rivest Cipher Encryption},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2024.0150858},
url = {http://dx.doi.org/10.14569/IJACSA.2024.0150858},
year = {2024},
publisher = {The Science and Information Organization},
volume = {15},
number = {8},
author = {Longyang Du and Tian Xie}
}
Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.