Open Access

ARTICLE

Intelligent Tunicate Swarm-Optimization-Algorithm-Based Lightweight Security Mechanism in Internet of Health Things

Gia Nhu Nguyen^1,2, Nin Ho Le Viet^1,2, Gyanendra Prasad Joshi³, Bhanu Shrestha^4,*

1 Faculty of Information Technology, Duy Tan University, Da Nang, 550000, Vietnam
2 Graduate School, Duy Tan University, Da Nang, 550000, Vietnam
3 Department of Computer Science and Engineering, Sejong University, Seoul, 05006, South Korea
4 Department of Electronic Engineering, Kwangwoon University, Seoul, 01897, South Korea

* Corresponding Author: Bhanu Shrestha. Email:

(This article belongs to the Special Issue: Intelligent Decision Support Systems for Complex Healthcare Applications)

Computers, Materials & Continua 2021, 66(1), 551-562. https://doi.org/10.32604/cmc.2020.012441

Received 01 July 2020; Accepted 30 August 2020; Issue published 30 October 2020

Abstract

Fog computing in the Internet of Health Things (IoHT) is promising owing to the increasing need for energy- and latency-optimized health sector provisioning. Additionally, clinical data (particularly, medical image data) are a delicate, highly protected resource that should be utilized in an effective and responsible manner to fulfil consumer needs. Herein, we propose an energy-effi- cient fog-based IoHT with a tunicate swarm-optimization-(TSO)-based lightweight Simon cipher to enhance the energy efficiency at the fog layer and the security of data stored at the cloud server. The proposed Simon cipher uses the TSO algorithm to select the optimal keys that will minimize the deterioration of quality between the original and reconstructed (decrypted) images. In this study, the decrypted image quality is preserved by the peak signal-to-noise ratio (PSNR) such that consumers can generate precise medical reports from IoHT devices at the application level. Moreover, a lightweight encryption step is implemented in the fog to improve energy efficiency and reduce additional computations at the cloud server. Experimental results indicate that the TSO-Simon model achieved a high PSNR of 61.37 dB and a pixel change rate of 95.31.

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Citations