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ARTICLE
ECG Encryption Enhancement Technique with Multiple Layers of AES and DNA Computing
1 BIOCORE Research Group, Faculty of Information & Communication Technology, Universiti Teknikal Malaysia Melaka, Melaka, 76100, Malaysia
2 Computer Science Department, College of Computer Science and Information Technology, University of Wasit, Wasit, Iraq
* Corresponding Author: Jamal Kh-Madhloom. Email:
(This article belongs to the Special Issue: Computational Intelligence for Internet of Medical Things and Big Data Analytics)
Intelligent Automation & Soft Computing 2021, 28(2), 493-512. https://doi.org/10.32604/iasc.2021.015129
Received 07 November 2020; Accepted 23 January 2021; Issue published 01 April 2021
Abstract
Over the decades, protecting the privacy of a health cloud using the design of a fog computing network is a very important field and will be more important in the near future. Current Internet of Things (IoT) research includes security and privacy due to their extreme importance in any growing technology that involves the implementation of cryptographic Internet communications (ICs) for protected IC applications such as fog computing and cloud computing devices. In addition, the implementation of public-key cryptography for IoT-based DNA sequence testing devices requires considerable expertise. Any key can be broken by using a brute-force attack with ample computing power. Therefore, establishing a model of DNA cryptography is extremely necessary to improve the interaction between current and new technologies. In addition, the implementation of public-key cryptography for IoT-based DNA sequence testing devices requires considerable expertise. The proposed algorithm can create a stable hybrid encryption algorithm based on DNA layers and advanced encryption standard (AES) to shorten encryption time and increase protection capacity to suit the IoT health cloud systems. The proposed model can protect the DNA sequence over the fog computing cloud against plain text attacks by generating (I) main key, which is the key to the EAES encryption algorithm; (II) Rule 1 key, which represents the DNA base number of possible key probabilities; and (III) Rule 2 key, which represents the number of binding probabilities of the DNA helical structure. This key is built to achieve higher levels of protection. An ECG encryption enhancement technique with multilayer AES and DNA computing (MLAESDNA) is proposed in this study. Results show that MLAESDNA can secure IoT signals via cloud computing.Keywords
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